Job Responsibilities:

• Design and implement data integration solutions to ingest, transform, and integrate structured and unstructured data from various sources into a scalable data architecture platform
• Develop, construct, and maintain large-scale data processing systems that collect data from variety of structured and unstructured data sources
• Store data in a scale-out data lake and prepare the data techniques in preparation for the data science data exploration and analytic modeling
• Ingest, transform, and blend/integrate structured and unstructured data and deliver the data to a MDM, data warehouse, and/or data lake
• Include both technical processes and business logic to transform data from disparate sources into cohesive meaningful data with quality, governance, and compliance considerations
• Use technical and business processes to combine data from disparate sources into meaningful and valuable information
• Design, build, and manage the information and big data infrastructure that helps analyze and process data that the organization requires and optimize systems to perform smoothly
• Prepare the data for the data scientist's exploration and discovery process
• Evaluate, compare, and improve the different approaches including design patterns innovation, data lifecycle design, data ontology alignment, annotated datasets, and elastic search approach

Job Requirements:

• University degree in Computer Science, Engineering, and/or a technically oriented field
• Over 5 years of experience with Flink/Spark, Databricks
• Over 5 years of experience with Azure (DP200 and/or DP201, DP203 certification acts as a plus)
• 3+ years' experience mining data as a data analyst
• 3+ years' using programming languages such as Java, DAX, MDX, SQL, Python
• 3+ years of experience with PowerBI, Tableau, or Qlik
• 3+ years' experience in the life insurance domain is required
• Passionate about analytics, machine learning technology, and applications, and eager to learn
• English communication

Knowledge and Skill:

• Good knowledge of Big Data technologies, such as Spark, Hadoop/MapReduce
• Good knowledge of Azure services like Storage Account, Azure DataBricks, etc.
• Good knowledge of SQL and excellent coding skills
• Strong knowledge of data modeling and data mining
• Self-Development, communication, problem-Solving Skills
• Open-minded, multi-tasking, teamwork, flexible, and interest to learn new things

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You’ll be working on some of the most exciting big data and AI open-source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love.

Responsibilities:

• Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications
• Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling, and remote shuffling
• Work with internal customers on critical business use cases that rely on big data
• Provide thought leadership to the entire company on how data should be processed and stored more reliably, quickly, and efficiently at scale
• Contribute to the team’s technical vision and long-term roadmap

Requirements:

• 12+ years of industry experience with a proven track record of technical excellence
• 8+ years of experience building and supporting large scalable Kubernetes or big data platforms
• Deep knowledge of big data / ML technologies (e.g., Flink, Spark, Presto, Kubernetes, Ray, PyTorch/TensorFlow)
• Proficiency in one or more programming languages (Java, Go, Scala, Python)
• Experience with Kubernetes and AWS technologies
• Exceptional collaboration skills with cross-functional partners, with the ability to navigate ambiguity, make trade-offs, and keep stakeholders aligned on priorities and progress.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent experience.

Benefits:

• Salary range: $242,634-$499,541 USD
• Eligible for equity

In-office requirement: This role will need to be in the office for in-person collaboration 1-2 times/quarter.

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Responsibilities

Architecture & Strategy

• Define the overall data platform architecture on OpenShift, covering ingestion (Kafka/Redpanda), compute (Spark, Flink, Trino), storage (MinIO, Iceberg), catalog (Polaris/Gravitino), orchestration (Airflow/Dagster), and serving (StarRocks/ClickHouse).
• Design the Data Lakehouse architecture: open table formats (Iceberg, Delta Lake), catalog federation, multi-engine interoperability.
• Architect the real-time data path: Kafka topic design, schema registry (Apicurio/Confluent), stream processing (Flink/Spark Structured Streaming).
• Design the analytical serving layer: OLAP engine selection (StarRocks/ClickHouse/Doris), materialized view strategy, query federation with Trino.
• Design multi-tenancy, data security (Ranger/OpenPolicyAgent), RBAC, and governance (DataHub/Atlas) across all platform layers.
• Set technical standards for Helm chart design, CI/CD pipelines, and GitOps (ArgoCD/Flux) workflows.

Technical Leadership

• Lead a team of 3–6 data platform engineers; run code reviews, design reviews, and sprint planning.
• Establish engineering best practices: testing, observability (OpenTelemetry, Prometheus, Grafana, Loki), incident response, runbooks.
• Partner with data engineering, analytics, and business teams to translate their needs into platform capabilities.
• Define platform SLOs/SLIs across freshness, latency, availability, and durability; drive the on-call rotation and incident post-mortems.

Hands-on Engineering

• Build and maintain the core OpenShift infrastructure: operators, Helm charts, namespaces, RBAC, network policies.
• Develop Spark and Flink job frameworks, tuning guides, workload scheduling (YuniKorn/Volcano).
• Implement the data mesh or data product model: domain ownership, self-serve data infrastructure, federated governance.
• Performance-optimize across the stack: Kafka throughput, Spark shuffle, Iceberg compaction, Trino query planning, OLAP cold reads.

Required Skills & Experience

• 10+ years in data/platform engineering, with 3+ years as architect or tech lead.
• Deep Kubernetes/OpenShift: operators, Helm, CRDs, admission webhooks, SCC, multi-tenancy at production scale.
• Expert-level streaming: Kafka/Redpanda internals (partitioning, consumer groups, exactly-once semantics), schema registry, Kafka Connect.
• Expert-level batch & streaming compute: Spark internals (Catalyst, Tungsten, AQE, shuffle, dynamic allocation), Flink or Spark Structured Streaming.
• Strong open table format knowledge: Iceberg and/or Delta Lake , table format internals, metadata evolution, partitioning transforms, maintenance, catalog integration (Polaris, Gravitino, Nessie, or Unity Catalog).
• Hands-on with federated query engines: Trino (coordinator/worker architecture, connector ecosystem, fault-tolerant execution mode).
• Solid OLAP knowledge: StarRocks, ClickHouse, or Apache Doris , primary key models, materialized views, query optimization.
• Production MinIO/S3-compatible storage at scale: erasure coding, multi-site replication, IAM, tiering.
• Pipeline orchestration: Airflow (DAG design, sensors, dynamic task mapping) or Dagster.
• Infrastructure-as-code (Terraform/Pulumi/Crossplane) and GitOps (ArgoCD/Flux).
• Fluent in at least one JVM language (Scala/Java) and Python.

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The Ads organization powers Reddit's advertising platform, enabling advertisers to reach highly engaged communities while helping Reddit grow its business. The reliability of our Ads systems directly impacts advertiser success, revenue generation, and user experience.

We're looking for a Staff Site Reliability Engineer who will define and provide technical leadership for reliability initiatives across the Ads organization and help shape the future of Ads infrastructure at Reddit.

Responsibilities:

• Lead reliability initiatives across multiple Ads domains including ad serving, auctions, targeting, reporting, measurement, and billing.
• Partner with engineering leadership to develop a roadmap to improve reliability, scalability, operational excellence, and engineering efficiency across the Ads organization.
• Design and build platforms, tooling, and automation that improve reliability and developer productivity at scale.
• Drive architecture reviews and influence technical decisions impacting critical revenue-generating systems.
• Participate in on-call rotations, lead complex incident investigations and coordinate cross-functional response efforts during major production events.
• Identify systemic reliability risks and drive long-term solutions that improve platform resilience.
• Establish reliability metrics around advertiser-critical user journeys such as campaign creation, ad delivery, auction participation, reporting, attribution, and billing.
• Mentor engineers and provide technical leadership across multiple teams.
• Influence roadmap planning and ensure reliability considerations are incorporated into product and infrastructure investments.

Requirements:

• 8+ years of experience in Site Reliability Engineering, Infrastructure Engineering, or related roles operating large scale distributed systems.
• Strong experience evolving high traffic, user-facing production environments.
• Strong cross-functional collaborations skills to lead and influence projects driving operational excellence.
• Deep expertise in modern distributed systems, scale engineering, and cloud-native architectures.
• Experience designing highly-available systems with strong operational and reliability practices.
• Strong software engineering skills in languages like general-purpose backend languages like Go.
• Strong understanding of observability systems including metrics, logging, tracing, and alerting.
• Experience improving reliability through SLOs, automation, incident management, and performance optimization.
• Demonstrated ability to troubleshoot complex issues across a modern distributed system stack.
• Strong collaboration and communication skills with the ability to influence technical direction across teams.

Nice to Have:

• Experience supporting advertising technology platforms or other large-scale revenue-critical systems.
• Deep understanding of reliability challenges associated with ad-serving, real-time auctions, budget pacing, campaign delivery, measurement, attribution, or billing systems.
• Experience operating high-QPS, low-latency services where latency directly impacts business outcomes.
• Experience establishing reliability programs that deliver meaningful, measurable business outcomes.
• Experience with Kubernetes, cloud infrastructure, and large-scale distributed systems.
• Familiarity with Kafka, ClickHouse, Spark, Flink, BigQuery, or similar large-scale data platforms.
• Experience partnering with Product, Data Science, and Ads Engineering organizations.
• Experience supporting machine learning inference or recommendation systems at scale.

Benefits:

• Comprehensive Health benefits
• 401k Matching
• Workspace benefits for your home office
• Personal & Professional development funds
• Family Planning Support
• Flexible Vacation & Reddit Global Days Off
• 4+ months paid Parental Leave
• Paid Volunteer time off

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This role owns the systems connecting Data Acquisition → Governance & Compliance → Curation → Training → Evaluation → Failure Mining → Data Improvement.

A critical part of the role is enabling aggressive data iteration while ensuring that every dataset is secure, policy-compliant, rights-aware, traceable, and auditable.

Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location.

This role is part of Microsoft AI’s Superintelligence Team, created to push the boundaries of AI toward Humanist Superintelligence,ultra-capable systems that remain controllable, safety-aligned, and anchored to human values.

Responsibilities

• Build 1P & 3P Data Flywheel Infrastructure: scalable systems for ingesting, processing, curating, versioning, and serving first-party and third-party data for pre-training and post-training.
• Own Data Governance, Security & Compliance Infrastructure: build governance and policy enforcement directly into the data platform.
• Build Policy-Aware Data Acquisition & Curation Systems: develop automated pipelines for 1P and 3P data ingestion, classification, filtering, deduplication, quality scoring, semantic enrichment, and dataset construction.
• Build Evaluation-to-Data Feedback Loops: convert model evaluations and real-world failure signals into actionable data tasks.
• Build Synthetic & AI-Native Data Pipelines: use LLMs, VLMs, and Agents to automate data generation, labeling, filtering, quality validation, enrichment, and transformation.
• Build Data Quality, Attribution & Observability: develop metrics and infrastructure to measure dataset quality, coverage, diversity, contamination, duplication, policy compliance, and contribution to model capability improvements.

Qualifications

• Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.
• Software Engineering experience using Python, SQL, Spark/Flink/Ray.

Preferred Qualifications

• Experience managing third-party datasets, data partnerships, licensed content, or externally sourced data with complex contractual and usage restrictions.
• Experience building privacy- and security-aware systems for first-party product or user data, including isolation, access controls, retention/deletion, and purpose limitation.
• Experience with data clean rooms, privacy-preserving processing, de-identification, confidential computing, or secure data collaboration.
• Experience building evaluation → failure mining → data generation → training feedback loops.
• Experience with synthetic data, model graders, reward signals, hard-example mining, active learning, or data-mixture optimization.
• Experience with multimodal or agentic datasets including text, image, video, audio, web, GUI, tool-use, or interaction trajectories.
• Understanding of Modern LLM training workflows including Pre-training, SFT, RL/post-training, evaluation, and synthetic data.
• Strong understanding of data governance, security, privacy, provenance, access control, and data lifecycle management.

Salary Information

Data Engineering IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. Data Engineering IC6 – The typical base pay range for this role across the U.S. is USD $165,600 – $296,400 per year.

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This role owns the systems connecting Data Acquisition → Governance & Compliance → Curation → Training → Evaluation → Failure Mining → Data Improvement.

A critical part of the role is enabling aggressive data iteration while ensuring that every dataset is secure, policy-compliant, rights-aware, traceable, and auditable.

The MAIST is a startup-like team inside Microsoft AI, created to push the boundaries of AI toward Humanist Superintelligence,ultra-capable systems that remain controllable, safety-aligned, and anchored to human values.

Responsibilities:

• Build 1P & 3P Data Flywheel Infrastructure
• Own Data Governance, Security & Compliance Infrastructure
• Build Policy-Aware Data Acquisition & Curation Systems
• Build Evaluation-to-Data Feedback Loops
• Build Synthetic & AI-Native Data Pipelines
• Build Data Quality, Attribution & Observability

Qualifications:

• Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering
• Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering
• Software Engineering experience using Python, SQL, Spark/Flink/Ray

Preferred Qualifications:

• Experience managing third-party datasets, data partnerships, licensed content, or externally sourced data with complex contractual and usage restrictions.
• Experience building privacy- and security-aware systems for first-party product or user data, including isolation, access controls, retention/deletion, and purpose limitation.
• Experience with data clean rooms, privacy-preserving processing, de-identification, confidential computing, or secure data collaboration.
• Experience building evaluation → failure mining → data generation → training feedback loops.
• Experience with synthetic data, model graders, reward signals, hard-example mining, active learning, or data-mixture optimization.
• Experience with multimodal or agentic datasets including text, image, video, audio, web, GUI, tool-use, or interaction trajectories.
• Understanding of Modern LLM training workflows including Pre-training, SFT, RL/post-training, evaluation, and synthetic data.
• Strong understanding of data governance, security, privacy, provenance, access control, and data lifecycle management.

Data Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year.

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We're looking for a senior staff software engineer to lead the next generation of data infrastructure at Pinterest which powers mission critical big data and AI applications. You’ll be working on some of the most exciting big data and AI open source technologies (Flink, Spark, Kubernetes, etc.), at the scale of exabytes of data to help Pinners discover and do what they love.

Responsibilities:

• Lead the strategy and technical direction of Pinterest’s data infrastructure for big data and AI applications
• Build and scale data infra frameworks and infrastructure to process petabytes-scale datasets, including compute engines, job management, resource management, scheduling and remote shuffling
• Work with internal customers on critical business use cases that rely on big data
• Provide thought leadership to the entire company on how data should be processed and stored more reliably, quickly and efficiently at scale
• Contribute to the team’s technical vision and long-term roadmap

Requirements:

• 10+ years of industry experience with a proven track record of technical excellence
• 5+ years of experience of building and support large scalable Kubernetes or big data platform
• Deep knowledge of big data / ML technologies (e.g. Flink, Spark, Presto, Kubernetes, Ray, PyTorch/TensorFlow)
• Proficiency in one or more programming languages (Java, Go, Scala, Python)
• Experiences in Kubernetes and AWS technologies
• Exceptional collaboration skills with cross-functional partners, with the ability to navigate ambiguity, make tradeoffs, and keep stakeholders aligned on priorities and progress.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent experience.

In-Office Requirement Statement: We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

• This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement: This position is not eligible for relocation assistance.

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The Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate.

Responsibilities:

• Own the technical strategy for the end-to-end Ads ML engineer lifecycle, starting with feature development, training data, offline experimentation, and model iteration workflows.
• Align Ads ML platform priorities with Reddit's broader ML Platform vision, translating Ads pain points into reusable platform capabilities where appropriate.
• Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency.
• Stay close to ML engineers and platform customers to identify high-leverage friction points and improve day-to-day development velocity.
• Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and more self-service.
• Over time, extend the platform strategy into serving and online experimentation workflows, creating a more seamless offline-to-online ML development experience.
• Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership, resolve ambiguity, and drive durable execution.
• Mentor Staff and senior engineers, raise the architecture and operational bar, and help grow the next generation of technical leaders.

Requirements:

• 8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems.
• 4+ years building or operating production ML infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines.
• Experience leading broad, ambiguous, multi-team platform initiatives from strategy through adoption.
• Experience building platforms used directly by ML engineers, data scientists, or product teams developing production ML systems.
• Deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure.
• Experience working with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies.

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

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At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

The Data Product Platform is mission-critical to accelerate data-driven decision-making at Pinterest on the foundation of 100s of thousands of tables and an exadata-scale data warehouse.

We are seeking a Staff Software Engineer to provide technical leadership and contribute to the development of solutions across both these pillars.

In this role, you will shape the vision and drive the execution of the solutions that handle increasing data volume, navigate business complexity, accelerate analytical velocity, and build the foundation for our next generation of agentic analytics products.

Responsibilities:

• Define and design Pinterest's data warehouse architecture, storage, and access patterns.
• Lead ambiguous, highly challenging, and cross-functional initiatives across the data warehouse and agentic data analytics domains.
• Mentor and elevate the technical bar for engineers, providing leadership on complex technical design, execution strategies, and critical trade-off decisions.
• Collaborate with stakeholders across Product, Data Science, and Engineering teams to understand user needs, drive alignment and drive progress.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 8+ years of relevant industry experience with large scale data warehouses, data tools and platforms.
• 5+ years experience building data warehouses and tools around the data ecosystem with technologies such as Spark, Trino, Flink, Airflow, Querybook, Superset, DataHub, etc.
• Ability to work with cross-functional partners across multiple organizations.
• Hands-on experience building tools and data pipelines leveraging AI coding tools, e.g. Cursor, Claude Code, Codex, etc.
• Hands-on experience building AI tools and platforms to accelerate data pipeline authoring, data analytics and engineering productivity.

Benefits:

• Salary range: $177,185-$364,795 USD
• Equity eligibility

#LI-REMOTE #LI-AH2

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This role combines strong software engineering practices with expertise in large-scale data processing and advanced analytical methods to deliver reliable, scalable solutions across the organization.

Responsibilities:

• Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc.
• Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement.
• Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows.
• Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights.
• Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics.
• Implement monitoring, alerting, and automation for data systems to support real-time decision support.
• Mentor team members on best practices for scalable data engineering and quantitative problem-solving.

Basic Qualifications:

• 4+ years of experience building production data pipelines and infrastructure at scale.
• Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).
• Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
• Solid understanding of cloud services for data storage, processing, and orchestration.
• Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
• Excellent problem-solving skills with a focus on delivering business impact through reliable systems.

Preferred Skills and Experience:

• Prior work in consumer technology, or social media domains.
• Experience with real-time streaming systems and low-latency data processing.
• Contributions to open-source data tools or publications on large-scale analytics systems.
• Track record of reducing operational costs or improving system efficiency through data optimizations.
• Ability to bridge engineering excellence with rigorous analytical approaches.

Compensation and Benefits:

The salary range is $180,000 - $440,000 USD. The total rewards package at xAI also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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We are seeking a skilled Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making.

Responsibilities:

• Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc.
• Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement.
• Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows.
• Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights.
• Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics.
• Implement monitoring, alerting, and automation for data systems to support real-time decision support.
• Mentor team members on best practices for scalable data engineering and quantitative problem-solving.

Basic Qualifications:

• 4+ years of experience building production data pipelines and infrastructure at scale.
• Strong proficiency in Python, SQL, and distributed computing frameworks (e.g., Spark, Flink, Hadoop).
• Demonstrated expertise in statistical methods, predictive modeling, hypothesis testing, and experimental design.
• Solid understanding of cloud services for data storage, processing, and orchestration.
• Bachelor's or Master's degree in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
• Excellent problem-solving skills with a focus on delivering business impact through reliable systems.

Preferred Skills and Experience:

• Prior work in consumer technology or social media domains.
• Experience with real-time streaming systems and low-latency data processing.
• Contributions to open-source data tools or publications on large-scale analytics systems.
• Track record of reducing operational costs or improving system efficiency through data optimizations.
• Ability to bridge engineering excellence with rigorous analytical approaches.

Compensation and Benefits:

The salary range is $180,000 - $440,000 USD. The total rewards package at xAI also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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Who we are

Stripe is a financial infrastructure platform for businesses. Millions of companies,from the world’s largest enterprises to the most ambitious startups,use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.

About the team

Data Quality and Governance owns the infrastructure that makes Stripe's data trustworthy and findable - the Data Catalog, the Knowledge Graph Service, dataset tiering and governance standards, lineage tracking, and the quality scoring system (DQPD) that every engineering team reports against. They're the team that defines what "good data" means at Stripe and then builds the enforcement and measurement tools to drive adoption across the company.

Responsibilities

• Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success
• Build and operate large-scale data discovery, metadata, or catalog platform
• Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders
• Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team

Who you are

We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply.

Minimum requirements

• This is a Staff-level role , that typically means 10+ years of experience building and operating data systems, pipelines, warehouses, infrastructure, and leading teams to deliver exceptional solutions
• Strong distributed systems fundamentals are a must , this team's core services are high-availability infrastructure that the rest of Stripe's data tooling depends on
• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
• Extreme customer focus, with a commitment to partnering with product, leaders across the business, and other Stripe engineers to understand their use cases
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs
• Thrive with high autonomy and responsibility in an ambiguous environment
• Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment

Preferred qualifications

• Our stack is made up of Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, and AWS Cloud - experience with all or some of these tools is a huge plus
• Influencing open-source contributions
• Experience creating and maintaining data marts / warehouses to power business reporting needs
• Experience collaborating with Product, Go-To-Market, or Sales / Marketing teams
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide

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Who we are

Stripe is a financial infrastructure platform for businesses. Millions of companies,from the world’s largest enterprises to the most ambitious startups,use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead.

About the team

We are experts in business data, building the canonical data foundation that powers decision-making across Finance & Strategy, Business Data Science, GTM, and Marketing. We engineer scalable and efficient data pipelines and provide curated data products that give Stripe's teams a consistent, accurate, and fresh view of the business,from the top to the bottom of the funnel.

What you’ll do

We're looking for a person who could contribute to the team by solving high-impact, cutting-edge data problems. The ideal candidate will be someone that has built data pipelines for large scale volume, is deeply knowledgeable of key tools including Airflow/Spark/Kafka/Flink, is empathetic, excels at building strong relationships, and collaborates effectively with other Stripe teams to understand their use cases and unlock new capabilities.

Responsibilities

• Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success
• Partner with our recruiting team to attract and hire top talent
• Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency
• Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders
• Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team

Who you are

Minimum requirements

• This is a Staff-level role , that typically means 10+ years of experience building and operating data systems, pipelines, warehouses, infrastructure, and leading teams to deliver exceptional solutions
• A strong engineering background and passion for data as well as prior experience with writing and debugging data pipelines using a distributed data framework
• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
• Extreme customer focus, with a commitment to partnering with product, leaders across the business, and other Stripe engineers to understand their use cases
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs
• Thrive with high autonomy and responsibility in an ambiguous environment
• Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment

Preferred qualifications

• Our stack is made up of Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, and AWS Cloud - experience with all or some of these tools is a huge plus
• Influencing open-source contributions
• Experience creating and maintaining data marts / warehouses to power business reporting needs
• Experience collaborating with Product, Go-To-Market, or Sales / Marketing teams
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide

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Stripe is a financial infrastructure platform for businesses. Millions of companies,from the world’s largest enterprises to the most ambitious startups,use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet.

About the Team

Product and Risk Data Engineering is Stripe's single source of truth data engineering layer for Payments, Risk, and Product , we enable Stripe to confidently run, measure, and grow the business by making accurate information easy to access.

Responsibilities

• Lead the technical outcomes for a team of ambitious, talented engineers, providing mentorship, guidance, and support to ensure their success
• Partner with our recruiting team to attract and hire top talent
• Deliver cutting-edge data pipelines that scale to users' needs, focusing on reliability and efficiency
• Develop strong subject matter expertise and manage the SLAs of data pipelines and full stack web applications that support critical stakeholders
• Collaborate with product managers and peers across the company to create/improve canonical datasets and data warehouses, use golden paths, and ensure Stripes and customers are using trustworthy data
• Leverage AI/LLM and Agents at scale to produce and analyze high-quality data on ambiguous problems
• Have the opportunity to drive the execution of key data initiatives for Stripe, overseeing the entire development lifecycle from planning to delivery while maintaining high standards of quality and timely completion
• Foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team

Requirements

• This is a Staff-level role , that typically means 10+ years of experience building and operating data systems, pipelines, warehouses, infrastructure, and leading teams to deliver exceptional solutions
• A strong engineering background and passion for data as well as prior experience with writing and debugging data pipelines using a distributed data framework
• An inquisitive nature in diving into data inconsistencies to pinpoint issues, and resolve deep rooted data quality issues
• Knowledge of a backend development language (such as Scala, Java, or Go) and strong SQL experience
• Extreme customer focus, with a commitment to partnering with product, leaders across the business, and other Stripe engineers to understand their use cases
• Effective cross-functional collaboration, with the ability to think rigorously, communicate clearly, and make or coordinate difficult decisions and trade-offs
• Thrive with high autonomy and responsibility in an ambiguous environment
• Ability to foster and work in a healthy, inclusive, challenging, and supportive work environment

Preferred Qualifications

• Experience with Iceberg, Kafka, Change Data Capture, Flink, Spark, Airflow, Hive Metastore, Pinot, Trino, and AWS Cloud
• Influencing open-source contributions
• Experience creating and maintaining data marts / warehouses to power business reporting needs
• Experience collaborating with Product, Go-To-Market, or Sales / Marketing teams
• Genuine enjoyment of innovation and a deep interest in understanding how things work, with the ability to question and direct architectural decisions
• Strong written and verbal communication skills for various audiences, including leadership, users, and company-wide

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Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organisations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence.

This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.

Staff Software Reliability Engineer - Data Platform

About the Team

The Data Platform team is responsible for the foundational data services, systems, and data products for Okta that benefit our users. Today, the Data Platform team solves challenges and enables:

• Streaming analytics
• Interactive end-user reporting
• Data and ML platform for Okta to scale
• Telemetry of our products and data

Our elite team is fast, creative and flexible. We encourage ownership. We expect great things from our engineers and reward them with stimulating new projects, new technologies and the chance to have significant equity in a company. Okta is about to change the cloud computing landscape forever.

About the Position

This is an opportunity for experienced Software Reliability Engineers to join our fast growing Data Platform organisation that is passionate about scaling high volume, low-latency, distributed data-platform services & data products. In this role, you will get to work with engineers throughout the organisation to build foundational infrastructure that allows Okta to scale for years to come. As a member of the Data Platform team, you will be responsible for designing, building, and deploying the systems that power our data analytics and ML. Our analytics infrastructure stack sits on top of many modern technologies, including Kinesis, Flink, ElasticSearch, and Snowflake.

We are looking for experienced Software Engineers who can help design and own the building, deploying and optimising the streaming infrastructure. This project has a directive from engineering leadership to make OKTA a leader in the use of data and machine learning to improve end-user security and to expand that core-competency across the rest of engineering. You will have a sizable impact on the direction, design & implementation of the solutions to these problems.

Job Duties and Responsibilities:

• Design, implement and own data-intensive, high-performance, scalable platform components
• Work with engineering teams, architects and cross functional partners on the development of projects, design, and implementation
• Conduct and participate in design reviews, code reviews, analysis, and performance tuning
• Coach and mentor engineers to help scale up the engineering organisation
• Debug production issues across services and multiple levels of the stack
• Participate in the on-call rotation, and incident management

Required Knowledge, Skills, and Abilities:

• 5+ years of industry experience
• 2+ years of experience in object-oriented language, preferably Java
• Hands-on experience using a cloud-based distributed computing technologies including
• Messaging systems such as Kinesis, Kafka
• Data processing systems like Flink, Spark, Beam
• Storage & Compute systems such as Snowflake, Databricks, Hadoop
• Coordinators and schedulers like the ones in Kubernetes, Hadoop, Mesos
• Experience in developing and tuning highly scalable distributed systems
• Excellent grasp of software engineering principles
• Solid understanding of multithreading, garbage collection and memory management
• Experience with reliability engineering specifically in areas such as data quality, data observability and incident management

Nice to have

• Maintained security, encryption, identity management, or authentication infrastructure
• Leveraged major public cloud providers to build mission-critical, high volume services
• Hands-on experience in developing Data Integration applications for large scale (petabyte scale) environments with experience in both batch and online systems.
• Contributed to the development of distributed systems or used one or more at high volume or criticality such as Kafka or Hadoop
• Experience developing Kubernetes based services on AWS Stack

The annual base salary range for this position for candidates located in Canada is between:$160,000-$220,000 CAD The Okta Experience

• Supporting Your Well-Being
• Driving Social Impact
• Developing Talent and Fostering Connection + Community

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At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment.

In this role, you will lead the design and development of core data storage, streaming, caching, and indexing platforms and underlying systems. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies.

Responsibilities:

• Drive the design, implementation, and reliability of our foundational data platforms and systems, working closely with stakeholders and internal customers to understand and refine requirements.
• Collaborate with cross-functional teams to define, design, and deliver new features.
• Proactively identify opportunities for, and drive improvements to, current programming practices, including process enhancements and tool upgrades.
• Present technical information to teams and stakeholders, providing guidance and insight on development processes and technologies.

Requirements:

• 5+ years of full-time engineering experience, post-graduation with specialties in back-end systems, specifically related to building large-scale data storage, streaming, and warehousing systems.
• Experience in various database technologies (MongoDB, Postgres), streaming/processing solutions (Kinesis, Flink, Spark), indexing/caching (ElasticSearch, Redis), and various data query engines (Trino, Presto, Snowflake, etc.).
• Show a track record of mentoring and leading teams in successful projects.
• Possess excellent communication and collaboration skills, and the ability to translate complex technical concepts to non-technical stakeholders.
• Experience working fluently with standard containerization & deployment technologies like Kubernetes and various public cloud offerings.
• Extensive experience in software development and a deep understanding of distributed systems, cloud platforms and data systems.

Nice to haves:

• Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI).
• Experience scaling products at hyper-growth startups.
• Excitement to work with AI technologies.

Benefits: No benefits mentioned.

About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.

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The Data Engineering Team builds and operates the foundational data infrastructure powering analytics, AI, and operational decision-making across CoreWeave. We design resilient data pipelines, scalable lakehouse systems, and high-quality datasets that enable teams across Finance, HR, Operations, and Engineering to move faster and make smarter decisions.

We're seeking a Staff Data Engineer to define and drive the architecture of CoreWeave's enterprise data ecosystem. You will establish the modeling, semantic, governance, and platform standards that enable teams to build trusted and reusable data products at scale.

In this role, you will:

• Define the company-wide strategy for data modeling, semantic layers, enterprise metrics, and reusable data products.
• Set architectural standards for CoreWeave's lakehouse, including data organization, schemas, metadata, governance, and serving patterns.
• Design scalable frameworks for data quality, lineage, observability, access control, and policy enforcement.
• Lead the architecture of complex, cross-domain data systems spanning operational, financial, product, people, and infrastructure data.
• Establish durable data contracts, system boundaries, and reusable engineering patterns across teams.
• Identify and resolve systemic performance, reliability, and scalability constraints across the data ecosystem.
• Lead architecture reviews for high-impact initiatives and ensure alignment with the broader platform strategy.
• Evaluate and standardize core data technologies across processing, orchestration, cataloging, modeling, and metadata management.
• Mentor senior engineers and raise the quality of system design and technical decision-making across the organization.

Who You Are:

• 10+ years of experience in data engineering, software engineering, distributed systems, or data architecture roles.
• Demonstrated experience setting technical direction for data systems spanning multiple teams, business domains, or platforms.
• Deep expertise in enterprise analytical modeling, including dimensional, Data Vault, semantic modeling, and governed metrics.
• Experience designing and operating large-scale lakehouse or streamhouse architectures using technologies such as Apache Iceberg, Delta Lake, Apache Hudi, Apache Paimon, or Apache Fluss.
• Advanced knowledge of distributed OLAP, query, processing, and ingestion systems such as StarRocks, ClickHouse, Trino, Spark, Flink, or Kafka.
• Expert-level SQL and strong programming expertise in Python, Scala, Java, or Rust, with experience building production-grade data systems.
• Demonstrated experience implementing governance capabilities such as lineage, profiling, metadata management, data quality controls, access policies, or auditability.
• Demonstrated ability to independently turn ambiguous problem statements into clear technical direction and execution plans.
• Track record of leading cross-cutting architecture and establishing standards adopted across multiple engineering teams.

The base salary range for this role is $207,000 to $275,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program.

What We Offer:

• Medical, dental, and vision insurance - 100% paid for by CoreWeave
• Company-paid Life Insurance
• Voluntary supplemental life insurance
• Short and long-term disability insurance
• Flexible Spending Account
• Health Savings Account
• Tuition Reimbursement
• Ability to Participate in Employee Stock Purchase Program (ESPP)
• Mental Wellness Benefits through Spring Health
• Family-Forming support provided by Carrot
• Paid Parental Leave
• Flexible, full-service childcare support with Kinside
• 401(k) with a generous employer match
• Flexible PTO
• Catered lunch each day in our office and data center locations
• A casual work environment
• A work culture focused on innovative disruption

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As a Software Engineer in X Data, you will play a key role in providing comprehensive data solutions that serve a wide range of stakeholders, including end-users and internal teams.

Responsibilities

You will help build and operate a distributed data platform that powers hundreds of real-time and batch pipelines processing billions of events per day.

• Design, build, and operate production-grade real-time and batch pipelines that ingest, process, validate, and deliver data powering user-behavior insights and product decisions.
• Create shared datasets, fact tables, and internal data products that let other teams analyse, debug, and improve product performance.
• Prototype and build tooling that automates and accelerates internal data workflows , backfills, dashboards, report generation, and self-serve access to data.
• Own data correctness end to end: validate with output invariants, denominator reconciliation, and independent recomputation, and lead root-cause investigations when key metrics move unexpectedly.
• Move fluidly across query engines and frameworks, choosing the right tool and adapting quickly to new infrastructure and environments.
• Partner across product and business teams to surface where data gaps exist and prioritise the highest-impact opportunities for new data acquisition and improvement.
• Iterate quickly on feedback, shipping the smallest useful increment with a strong bias toward efficient, accurate, and reliable solutions.

Basic Qualifications

We are looking for an engineer with 3+ years of professional software engineering experience, ideally in data engineering or distributed systems.

• Hands-on expertise in Python, Rust, Scala, Go or Java, and data pipeline toolings and distributed systems.
• Knowledge of real-time and batch data processing tools such as Spark/Kafka/Flink/SQL and various storage systems in RMDBs/NoSQL.
• Experience solving large-scale problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements.
• Proven records of interpreting product requirements into engineering implementation plans, and effectively communicating with different groups.

Compensation and Benefits

$125,000 - $400,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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As a Software Engineer in X Data, you will play a key role in providing comprehensive data solutions that serve a wide range of stakeholders, including end-users and internal teams.

Responsibilities

You will help build and operate a distributed data platform that powers hundreds of real-time and batch pipelines processing billions of events per day.

• Design, build, and operate production-grade real-time and batch pipelines that ingest, process, validate, and deliver data powering user-behavior insights and product decisions.
• Create shared datasets, fact tables, and internal data products that let other teams analyse, debug, and improve product performance.
• Prototype and build tooling that automates and accelerates internal data workflows , backfills, dashboards, report generation, and self-serve access to data.
• Own data correctness end to end: validate with output invariants, denominator reconciliation, and independent recomputation, and lead root-cause investigations when key metrics move unexpectedly.
• Move fluidly across query engines and frameworks (e.g., BigQuery, Trino, Clickhouse for analytics; Flink, Kafka, Spark/Scalding for streaming and batch), choosing the right tool and adapting quickly to new infrastructure and environments.
• Partner across product and business teams to surface where data gaps exist and prioritise the highest-impact opportunities for new data acquisition and improvement.
• Iterate quickly on feedback, shipping the smallest useful increment with a strong bias toward efficient, accurate, and reliable solutions.

Basic Qualifications

• 3+ years of professional software engineering experience, ideally in data engineering or distributed systems.
• Hands-on expertise in Python, Rust, Scala, Go or Java, and data pipeline toolings and distributed systems.
• Knowledge of real-time and batch data processing tools such as Spark/Kafka/Flink/SQL and various storage systems in RMDBs/NoSQL.
• Experience solving large-scale problems and comfortable doing incremental quality work while building brand new systems to enable future quality improvements.
• Proven records of interpreting product requirements into engineering implementation plans, and effectively communicating with different groups (AI, product, marketing/sales and engineering).

Compensation and Benefits

$125,000 - $400,000 USD

Base salary is just one part of our total rewards package at xAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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We are looking for a Software Engineer to join the team. The successful candidate will help shape the future of Spotify's financial data platform by designing robust data models, developing scalable backend services, and building high-volume data pipelines.

Responsibilities

• Build, operate, and evolve scalable Scio data pipelines on Google Cloud Platform that process high-volume financial data with accuracy and reliability.
• Develop and enhance Java backend services that power integrations across Spotify's financial ecosystem.
• Design and evolve data models and datasets that support accounting, reconciliation, financial reporting, and operational insights.
• Build and improve integrations with external financial systems to bring critical financial data into Spotify's financial ecosystem.
• Partner closely with Finance, Product, and Engineering teams to translate accounting requirements into reliable, scalable technical solutions.
• Improve the scalability, observability, and resilience of financial data pipelines and backend services.
• Contribute to engineering best practices through continuous delivery, automated testing, monitoring, and thoughtful code reviews.
• Help drive technical decisions that improve the long-term maintainability of Spotify's financial engineering platform.

Requirements

• 3+ years of professional experience building backend systems and data-intensive applications.
• Experience with Scala or Java and at least one distributed data processing framework such as Scio, Apache Beam, Spark, or Flink.
• Knowledge of designing and building reliable backend services and scalable data pipelines that support business-critical workflows.
• Experience designing data models that enable accurate, high-volume financial processes.
• Experience working with workflow orchestration platforms such as Flyte, Airflow, or similar technologies.
• Strong engineering fundamentals, including continuous delivery, automated testing, monitoring, and writing production-quality code.
• Ability to collaborate with cross-functional partners and translate complex business requirements into elegant technical solutions.
• Experience working within financial, accounting, or other regulated data domains is a plus.
• A Bachelor's degree or higher in Computer Science or a related field is a plus.

Location and Benefits

• This role is based in Toronto.
• Flexible work arrangements available.
• Salary range: CAD 103,321.00–147,602.00, plus equity.
• Benefits include extended health and dental coverage, retirement savings plans, monthly meal allowance, 23 paid days off, 13 paid flexible holidays, and other benefits in accordance with Canadian employment standards.

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Responsibilities:

• Provide strategic technical leadership across engineering projects, ensuring alignment with business goals, architecture principles, and regulatory/compliance requirements.
• Architect and design scalable, resilient, secure microservices and event-driven systems to support high-throughput financial services workloads.
• Lead adoption and governance of engineering standards, patterns, and best practices (API design, domain-driven design, CI/CD).
• Hands-on development and code review in core platforms; set standards for software craftsmanship across Modern Tech stacks and cloud-native services.
• Mentor and coach senior engineers and engineering leads; run regular technical deep dives, architecture reviews, and cross-team workshops.
• Lead and facilitate blameless post-mortems and structured root cause analysis (RCA), driving remediation plans and lessons learned into the development lifecycle.
• Own the Tech Risk Control 'book of work': maintain backlog of control remediation tasks, coordinate with Risk/Compliance to define mitigations, track progress, and ensure audit readiness.
• Drive the integration of AI/ML capabilities into production systems with appropriate controls for governance, model risk, explainability, and data privacy.
• Collaborate with product, security, ops, and data teams to prioritise technical debt, reliability improvements, and platform investments.
• Represent engineering in stakeholder forums, technical governance boards, and external partner engagements.

What you will be doing:

• Act as the technical owner for core platform domains, driving architecture, design, and delivery across backend, data streaming, and cloud infrastructure; focus deeply on 2-3 areas (e.g., Java/Spring, Kafka/Stream Processing, Cloud/Kubernetes).
• Lead targeted technical deep-dives (2-3 per quarter) to resolve architectural trade-offs, eliminate chronic pain points, and transfer knowledge across teams.
• Own and deliver the Tech Risk Control book-of-work items for your area: define remediations, coordinate cross-functional delivery, produce evidence for audits, and close out controls.
• Run structured root-cause analysis and blameless post-mortems for major incidents, translate findings into prioritised fixes, and ensure follow-through.
• Provide hands-on technical direction: participate in design reviews, code reviews, prototyping, and proof-of-concepts to validate architecture decisions.
• Mentor senior engineers and engineering leads; raise team capability through coaching, workshops, and documented standards/patterns.
• Collaborate with product, security, data, and ops to align technical strategy with business objectives, regulatory requirements, and non-functional goals (scalability, resilience, security).
• Drive adoption of cloud-native and DevOps practices (CI/CD, observability) and ensure production readiness for new services and AI/ML components.

Qualifications Certifications & Education:

• University degree in Computer Science, Engineering, or related discipline; MSc/PhD preferred.
• Cloud certification(s) strongly preferred: AWS Certified Solutions Architect Professional or DevOps Engineer, Microsoft Certified: Azure Solutions Architect, or Google Professional Cloud Architect.
• Desirable: Kubernetes (CKA/CKAD), security or data governance certificates.

Preferred Qualifications:

• Experience in financial services or regulated industries with demonstrable knowledge of regulatory controls, audit preparation, and model risk governance.
• Contributions to open source projects or academic/industry research; speaker at technical conferences is a plus.
• Proven ability to lead cross-functional engineering teams through technological transformations, and to operationalise AI safely at scale.

Deliverables & Success Measures:

• Architecture and platform designs that meet non-functional requirements (scalability, resiliency, security).
• Successful delivery of prioritised Tech Risk Control book-of-work items and remediation actions.
• Reduction in incident mean-time-to-detect and mean-time-to-recover through improved observability, RCA, and runbooks.
• Mature AI/ML deployment pipelines with documented governance, monitoring, and model lifecycle controls.
• High team engagement, evidence of knowledge transfer via deep dive sessions, and measurable uplift in engineering capability.

Technical Skills & Experience:

• Strong Java expertise (Java 8/11/17/21/25), demonstrated through large-scale, production systems.
• Deep experience with Spring ecosystem: Spring Boot, Spring Cloud, Spring Security, Spring Data, and related tooling.
• Microservices and cloud-native architectures: containerisation (Docker), orchestration (Kubernetes), service mesh (Istio/Linkerd), and 12-factor app principles.
• Event streaming and messaging: Apache Kafka (Kafka Streams, ksqlDB), Confluent tooling, and best practices for exactly-once semantics and fault-tolerant processing.
• Data platform familiarity: batch/stream processing (Spark, Flink), data lakehouse concepts (Delta Lake), and data governance tools (e.g., Apache Atlas, Apache Falcon, or equivalent).
• AI/ML/LLM productionisation: hands-on with MLOps and Model frameworks (LangGraph, Agent Development Kit, Microsoft Agent Framework); experience deploying and operating LLMs (e.g., Falcon family or other LLMs), embeddings, RAG architectures, and frameworks (LangChain, LlamaIndex).
• Observability, reliability, and performance engineering: Prometheus/Grafana, ELK/EFK, distributed tracing (Jaeger/Zipkin), profiling, and tuning high-throughput systems.
• DevOps, CI/CD: Terraform, Ansible, G3, and SonarQube.
• Cloud platforms: proven experience on at least one major public cloud (AWS, Azure, or GCP) in production-scale environments.
• Security, compliance & risk controls: secure coding practices, threat modelling, encryption, key management, and OWASP mitigation patterns.

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By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly.

The Data Enablement Platform team owns and operates the systems required to deliver data to clients, and partners with them to create impactful data-backed products.

As a DEP team member, you will help build Brex's Data Infrastructure and work across the entire data stack to help product teams build data-backed products.

Responsibilities:

• Build, improve, and maintain Brex's data platform and infrastructure: data warehouse & analytics, data streaming, replication and materialization, data orchestration, data observability, access & governance.
• Partner with Brex's product teams, data science and analytics teams to help them launch superior products backed by data insights.
• Level up the data competency at Brex through partnership and education.
• Invest in building resilient data architectures, participate in on-call rotations, and continuously improve operational efficiency.

Requirements:

• 5+ years of professional experience in a data infra or data platform role
• Experience with one or more of Snowflake, Flink, Airflow, dbt, CDC
• Fluency in Kotlin or Kotlin-like development languages such as Python
• Experience building and maintaining large-scale modern data stack
• Experience with streaming infra like Kafka
• Experience in backend engineering or full-stack development
• Strong communication and collaboration skills, especially working across team boundaries and building XFN relationships

The expected salary range for this role is $192,000-$240,000 USD.

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By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly.

The Data Enablement Platform team owns and operates the systems required to deliver data to clients, and partners with them to create impactful data-backed products.

As a DEP team member, you will help build Brex's Data Infrastructure and work across the entire data stack to help product teams build data-backed products.

Responsibilities:

• Build, improve, and maintain Brex's data platform and infrastructure: data warehouse & analytics, data streaming, replication and materialization, data orchestration, data observability, access & governance.
• Partner with Brex's product teams, data science and analytics teams to help them launch superior products backed by data insights.
• Level up the data competency at Brex through partnership and education.
• Invest in building resilient data architectures, participate in on-call rotations, and continuously improve operational efficiency.

Requirements:

• 5+ years of professional experience in a data infra or data platform role.
• Experience with one or more of Snowflake, Flink, Airflow, dbt, CDC.
• Fluency in Kotlin or Kotlin-like development languages such as Python.
• Experience building and maintaining large-scale modern data stacks.
• Experience with streaming infra like Kafka.
• Experience in backend engineering or full-stack development.
• Strong communication and collaboration skills, especially working across team boundaries and building XFN relationships.

Bonus points:

• Experience collaborating with product teams or building full-stack data-backed products.
• Experience with data architecture and data strategy.

The expected salary range for this role is $192,000-$240,000 USD.

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The Data Enablement Platform team owns and operates the systems required to deliver data to our clients and partners with them to create impactful data-backed products. You will be responsible for building, improving, and maintaining Brex's data platform and infrastructure, including data warehouse & analytics, data streaming, replication and materialization, data orchestration, data observability, access & governance.

You will partner with Brex's product teams, data science, and analytics teams to help them launch superior products backed by data insights. Additionally, you will level up the data competency at Brex through partnership and education, invest in building resilient data architectures, participate in on-call rotations, and continuously improve our operational efficiency.

The expected salary range for this role is $192,000-$240,000 USD. The starting base pay will depend on a number of factors, including the candidate's location, skills, experience, market demands, and internal pay parity.

Responsibilities:

• Build, improve, and maintain Brex's data platform and infrastructure
• Partner with product teams, data science, and analytics teams to launch data-backed products
• Level up data competency at Brex through partnership and education
• Invest in building resilient data architectures and improve operational efficiency

Requirements:

• 5+ years of professional experience in a data infra or data platform role
• Experience with one or more of Snowflake, Flink, Airflow, dbt, CDC
• Fluency in Kotlin or Kotlin-like development languages such as Python
• Experience building and maintaining large-scale modern data stacks
• Experience with streaming infra like Kafka
• Experience in backend engineering or full-stack development
• Strong communication and collaboration skills

Bonus points:

• Experience collaborating with product teams or building full-stack data-backed products
• Experience with data architecture and data strategy

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As a Software Engineer on the Data Orchestration team at Stripe, you will design, build, and maintain innovative data platform products. You will work on a wide range of technologies including Airflow, Spark, SQL, Kafka, Flink, Hive MetaStore, Trino, Pinot, Python, Java, Scala, S3, and Iceberg.

Responsibilities

• Design, build, and maintain key Data Platform products with a focus on usability, reliability, security, and efficiency.
• Create ergonomic APIs and abstractions for internal Stripe users, enhancing their experience and that of millions of Stripe customers.
• Ensure operational excellence and high availability of the Data Orchestration platform across batch workloads.
• Collaborate with high-visibility teams to support their initiatives while building a robust platform benefiting all of Stripe.
• Plan for Stripe's infrastructure growth by unblocking and supporting internal partners.

Requirements

• 8+ years of professional experience writing high-quality production-level code with an interest in Data Infrastructure.
• Experience operating or enabling large-scale, high-availability data pipelines.
• Expertise in Spark, Flink, Airflow, Python, Java, SQL, and API design is a plus.
• Experience developing, maintaining, and debugging distributed systems built with open-source tools.
• Strong collaboration and communication skills.

Preferred Qualifications

• Experience writing production-level code in Scala, Spark, Flink, Airflow, Python, Java, and SQL.
• Experience designing APIs or building developer platforms.
• Experience optimizing the end-to-end performance of distributed systems.

Work Environment

Office-assigned Stripes spend at least 50% of their time in their local office or with users.

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The successful candidate will spearhead the definition and design of Pinterest's data warehouse architecture, storage, governance, and usage. They will set the strategic direction for world-class data analytics tools, define and drive the adoption of comprehensive data governance policies and tooling, and lead ambiguous, highly challenging, and cross-functional initiatives across the data ecosystem.

Responsibilities:

• Spearhead the definition and design of Pinterest's data warehouse architecture, storage, governance, and usage.
• Set the strategic direction for world-class data analytics tools, including experimentation platforms, ad hoc analysis systems, data visualization, data pipeline authoring, and AI-assisted data analytics capabilities.
• Define, design, and drive the adoption of comprehensive data governance policies and tooling to ensure data quality, promote responsible data handling, and maximize efficiency.
• Lead ambiguous, highly challenging, and cross-functional initiatives across the data ecosystem, expertly managing trade-offs among unique requirements and constraints to deliver a cohesive user experience.
• Drive measurable adoption and significant business impact across the entire product portfolio through platform and tooling initiatives.
• Mentor and elevate the technical bar for engineers, providing leadership on complex technical design, execution strategies, and critical trade-off decisions.
• Collaborate with stakeholders across Product, Data Science, and Engineering teams to understand user needs, drive alignment, and drive progress.

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience.
• 12+ years of relevant industry experience with large-scale data warehouses, data tools, and platforms.
• 5+ years of experience building data warehouses and tools around the data ecosystem with technologies such as Spark, Trino, Flink, Airflow, Querybook, Superset, DataHub, etc.
• Ability to work with cross-functional partners across multiple organizations.
• Hands-on experience building tools and data pipelines leveraging AI coding tools, e.g., Cursor, Claude Code, Codex, etc.
• Hands-on experience building AI tools and platforms to accelerate data pipeline authoring, data analytics, and engineering productivity.

Benefits:

• Salary range: $208,592-$429,454 USD
• Equity eligibility
• Flexible working model (PinFlex)
• Opportunity to work in-office 1-2 times/quarter

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The Product Security Data Platforms team is a newly established engineering team within Stripe Security. Our mission is to build the foundational infrastructure that provides our users with unprecedented visibility into the security posture of their Stripe integration. While Stripe is renowned for industry-leading payment protection, we are expanding our focus to provide a comprehensive security telemetry platform that helps businesses protect their entire digital ecosystem on Stripe.

As a founding member of this team, you will be architecting a large-scale customer-facing security data pipeline and presentation layer. Much like modern security observability platforms and data lakes that have transformed cloud infrastructure, we are building an API-first service that transforms massive streams of behavioral data into actionable security intelligence. This team operates at the intersection of high-throughput data engineering and cybersecurity, creating the systems that will allow the world’s most sophisticated companies to monitor, detect, and respond to threats in real-time.

Responsibilities

• Architect Scalable Foundations: Design and implement a highly available, low-latency pipeline capable of processing and augmenting millions of events per second into structured security telemetry.
• Build API-First Products: Develop the core services and streaming APIs that enable enterprise customers to seamlessly ingest security signals into their own internal security operations centers and analytics tools.
• Engineering Security Signals: Partner with security researchers and threat detection experts to build the logic that identifies anomalous behavior and surfaces high-fidelity security insights.
• Define Technical Strategy: Lead the technical roadmap for the platform, making critical decisions on data modeling, storage strategies, and the abstraction layers that will support future security products.
• Drive Engineering Excellence: As a senior leader, you will set the bar for code quality, system resilience, and operational maturity for a product that requires 99.99%+ availability.
• Cross-functional Collaboration: Work closely with Stripe’s core platform and data teams to leverage global infrastructure while ensuring security data remains isolated and protected.

Requirements

• 8+ years of professional software development experience, with a history of shipping and maintaining complex, large-scale systems.
• Expertise in Data Engineering & Distributed Systems: Deep experience building and operating high-throughput data pipelines (e.g., Kafka, Flink, Spark, or similar streaming technologies).
• Strong Programming Fundamentals: Significant experience in languages like Java, C++, or Rust.
• System Design Leadership: A proven track record of designing robust, scalable architectures and leading cross-team technical initiatives from conception to launch.
• Operational Mindset: Experience maintaining mission-critical services with high availability requirements, on-call rotation, and a strong focus on observability and debugging.
• Communication & Collaboration: Excellent technical writing skills for drafting design documents and the ability to mentor other engineers while collaborating with non-technical stakeholders.

Preferred Qualifications

• Security Domain Knowledge: Prior experience building security analytics, threat detection systems, or observability platforms.
• Platform Engineering: Experience building "as-a-service" infrastructure where the primary users are other engineers or external developers.
• Cloud Native Infrastructure: Prior experience with AWS, Kubernetes, and infrastructure-as-code (Terraform).
• Product Intuition: A desire to work on "0-to-1" initiatives where you help define the product requirements and user experience alongside engineering.
• Front-end / Full Stack Experience: Prior React / TypeScript frontend experience is helpful

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We are orchestrating a high-performing data team that works with pace and enthusiasm! Yuno moves money across borders for companies that can't afford for payments to fail. Our data platform is what makes that visible , to our product teams, our clients, and ourselves.

You will play a pivotal role within the Data team that powers Yuno and its payment platform, while helping co-design and implement an architecture that enables the entire organization to operate on reliable, fast, and trustworthy data.

Your Contribution Will Be

The stack is modern: StarRocks as our primary analytical layer, Flink for processing, DBT for transformation, Airflow for orchestration and various tooling for surfacing insights. The hard work of making it super reliable is still in front of us , and that's exactly why this role exists.

Technical Leadership

• Define architecture within the data platform, structure and deliver projects and initiatives end-to-end.
• Act as a technical reference point for the Data team, setting quality standards, testing, observability, data modeling, and documentation.
• Lead the design and implementation of scalable, low-latency data pipelines that process high-volume payment transactions in real time.
• Champion an AI-first engineering culture, establishing standards for AI-assisted development, automated data quality testing, and LLM-powered data workflows.

Hands-On Engineering

• Design and build data pipelines for large volumes of payment data that are performant, reliable, and correct , not just fast.
• Design scalable data models that support business-critical use cases: fraud detection, revenue analytics, payment success rate optimization, regulatory reporting.
• Own platform reliability , SLAs, data quality, alerting, and incident response for data services.
• Ensure secure data handling practices aligned with PCI-DSS, GDPR, and other compliance frameworks relevant to the payments industry.

Cross-Functional Impact

• Partner with Product, AI, and Finance teams to translate business needs into scalable data solutions.
• Contribute to the roadmap of the data platform and proactively identify opportunities to unlock new business value through data.
• Mentor senior and mid-level engineers, raising the technical bar across the team through code reviews, design reviews, and knowledge-sharing sessions.
• Collaborate with Data Consumers (analysts, data scientists, product managers) to ensure data products are reliable, well-documented, and fit for purpose.

Skills You Need

Minimum Qualifications

• 8+ years of experience in data engineering, software engineering, or a related field, with at least 2 years operating at a staff or principal level.
• Deep expertise in designing and building large-scale data platforms , streaming, batch, or hybrid architectures.
• Hands-on experience with Spark, Flink, Kafka, StarRocks, or equivalent.
• Strong Python and SQL skills; comfort working across multiple languages and paradigms.
• Solid understanding of data modeling techniques: dimensional modeling, Data Vault, or lakehouse patterns.
• Experience with cloud data infrastructure (AWS, GCP, or Azure), including managed services for storage, compute, and orchestration.
• Strong grasp of data quality, observability, and governance principles.
• Proven ability to set standards and lead technical initiatives across multiple teams without direct authority.
• Professional proficiency in English , written and spoken.

Preferred Qualifications

• Experience in the payments or fintech industry.
• Familiarity with dbt, Great Expectations, or similar.
• Experience with event-driven services and data mesh approaches.
• Exposure to ML platform design or feature store infrastructure.

What We Offer at Yuno

• Competitive Compensation.
• Remote Work – You can work from everywhere!
• Home Office Bonus – A one-time allowance to help you create your ideal home office.
• Work Equipment.
• Stock Options.
• Health Plan wherever you are.
• Flexible Days Off.
• Language, Professional, and Personal Growth courses.

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Responsibilities:

• Shape the team's long-term vision and roadmap in close collaboration with cross-functional partners across Airbnb
• Build strong relationships with partner engineering teams to drive aligned and impactful outcomes
• Design, develop, and maintain reliable, scalable data pipelines - both batch and real-time - that collect, process, and serve data from diverse sources across Airbnb
• Implement robust offline and online feature building processes to enable faster production of ML products
• Architect and build ML infra and optimize for performance, scalability, and cost-effectiveness
• Mentor and develop engineers on the team, while also contributing to and influencing the broader data engineering community at Airbnb

Requirements:

• 9+ years of relevant industry experience with a Bachelor's and/or Master's degree in CS/EE, or equivalent experience, or 6+ years of experience with a PhD
• Strong CS fundamentals, and knowledge of architecture and common design patterns
• Experience running data processing pipelines in production using distributed data processing frameworks like Apache Spark or Flink
• Experience collaborating with client, backend, ml, analytics teams, product and business partners
• Effectively work across team boundaries to establish overarching data architecture, data flow, and provide guidance to individual teams
• Experience working on/with end-to-end Machine Learning products
• Excellent communication skills, both written and verbal

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Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime.

At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work.

Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think.

We’re looking for a Staff Software Engineer to help build the next generation of Pinterest’s big data storage platform. You’ll work on some of the most exciting big data open source technologies , especially Apache Iceberg , at exabyte scale to power the data infrastructure that helps Pinners discover and do what they love.

As a Staff Software Engineer, you’ll serve as a technical leader and hands-on contributor, designing and building highly scalable storage systems for Pinterest’s data lake. You’ll partner closely with teams across data, ML/AI, analytics, and infrastructure to evolve our storage and metadata management capabilities, enabling efficient, reliable, and governed access to data at massive scale.

What you’ll do:

• Design, implement, and optimize Pinterest’s exabyte-scale data lake storage platform.

• Lead complex technical projects and initiatives for data lake storage and metadata management, driving them from architecture through execution.

• Collaborate with stakeholders and partner teams across the organization to design storage and metadata layer technologies that unlock big data and ML/AI innovations.

• Build storage capabilities that efficiently support large-scale ML/AI workloads, including high-throughput data access, schema evolution, and large-scale column backfills.

• Shape the long-term technical direction for scalable, reliable, and efficient big data storage systems.

• Engage with and contribute to open source communities such as Apache Iceberg, Spark, and Flink to help address Pinterest’s scaling challenges.

What we’re looking for:

• 8+ years of relevant industry experience designing and building large-scale production distributed systems.

• Strong experience designing and maintaining scalable storage, metadata, or data lake infrastructure.

• Experience building storage capabilities for large-scale ML/AI or analytics workloads, including high-throughput data access, schema evolution, and large-scale column backfills.

• Deep knowledge with building distributed systems, data storage systems, and production infrastructure.

• Experience with big data technologies such as Apache Iceberg, Spark, Flink, Presto/Trino, Hive, or similar systems.

• Proficiency in programming languages like Java, Scala, or Python.

• Proven ability to lead complex technical initiatives and influence architecture across teams.

• Strong collaboration, communication, and problem-solving skills, with a drive for technical excellence and innovation.

• Bachelor’s degree in a relevant field such as Computer Science, or equivalent experience

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.

This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

This position is not eligible for relocation assistance.

Visit our PinFlex page to learn more about our working model.

#LI-HYBRID #LI-AH2

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise. Information regarding the culture at Pinterest and benefits available for this position can be found here.

US based applicants only

$177,185-$364,795 USD

Our Commitment to Inclusion:

Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.

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Design, build, and optimize robust ETL/ELT pipelines to reliably ingest, integrate, and transform diverse people data from various HR systems (HRIS, ATS, LMS, etc.) into our data platform.

Develop, maintain, and govern scalable and secure data models, schemas, and ontologies specifically for people analytics, ensuring data quality, consistency, and accessibility for downstream consumption.

Contribute to the strategic design, development, and evolution of our people data platform and tooling, advocating for engineering best practices, automation, and a scalable analytics ecosystem (e.g., leveraging SQLMesh, Iceberg, Flyte).

Partner closely with People Analysts, HR Business Partners, and other stakeholders to understand their analytical needs and translate them into robust data solutions, providing well-structured, documented, and reliable datasets.

Implement and monitor data quality checks, identify discrepancies, troubleshoot data issues, and ensure the reliability and integrity of people data across all systems.

Continuously monitor the performance of data pipelines and models, identifying bottlenecks and implementing solutions to ensure the efficiency and scalability of our people data infrastructure.

Create and maintain comprehensive documentation for data pipelines, models, and processes, and champion data engineering best practices (e.g., version control, testing, CI/CD) within the team.

Implement and enforce strict data security measures and ensure all data handling practices comply with internal policies and external regulations (e.g., GDPR, CCPA) related to employee data privacy.

Collaborate with broader enterprise analytics and data engineering teams to align on data architecture standards, integrate people data with other business domains, and contribute to the overall evolution of the company's data platform.

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Your primary responsibilities will include:

• Installing, configuring, and maintaining database management systems (DBMS) and related software
• Monitoring and optimizing database performance to ensure efficient and reliable operations
• Developing and implementing database backup and recovery plans, as well as disaster recovery plans
• Managing and monitoring database security, ensuring that all sensitive data is protected
• Troubleshooting and resolving database issues, including performance, connectivity, and data integrity issues
• Developing and maintaining database documentation, including data models, database schemas, and system architecture diagrams

In this role, you will have the opportunity to work closely with our software developers and other IT staff to design and develop database systems that meet the needs of our growing business.

If you are a motivated and experienced database professional looking for a new challenge, we encourage you to apply.

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$293K – $325K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

At OpenAI, we’re building the connective tissue between our mission and our people. People Innovation Labs is a fast-moving engineering team embedded in the People organization, focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we’re designing systems that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation.

About the Role

We are looking for a hands-on engineering manager to lead technical and product strategy and execution for People Innovation Labs’ OpenHouse pod. OpenHouse is our flagship employee-facing product, serving as a culture and communication hub and an organization-wide front door into all other aspects of People Innovation Labs’ work. The OpenHouse pod is composed of full stack product engineers who are deeply curious about culture, recruiting and people development, and want to know everything from the business strategy and metrics down through the code that gets us there. In this role, you will work with People Innovation Labs leadership to build and grow the team and OpenHouse product, innovating on how we apply LLMs along the way.

We’re seeking a Data Engineer to build data-intensive systems that will power People Innovation Labs’ internal products and enable the People Analytics function to do their best work. These data pipelines are crucial for our build-out of people products backed by business systems of record and for ongoing people data analytics.

One example of an employee-facing product you’ll help us build is OpenHouse, which serves as a culture and communication hub and an organization-wide front door into all other aspects of People Innovation Labs’ work. OpenHouse and other products in our portfolio are built by full stack product engineers who are deeply curious about culture, recruiting and people development, and want to know everything from the business strategy and metrics down through the code that gets us there. In this role, you will work with People Innovation Labs leadership and software engineers and the People Analytics team to build the data systems that enable this work.

In this role, you will:

• Design, build and manage people data pipelines, ensuring all data is seamlessly integrated into our Databricks warehouse.

• Develop canonical datasets to track key people metrics and People Innovation Labs product metrics.

• Work collaboratively with various teams, including, Data Platform, Data Science, People Analytics, and Compensation and Equity to understand their data needs and provide solutions.

• Implement robust and fault-tolerant systems for data ingestion and processing.

• Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear as the primary data engineering expert on the team.

• Ensure the security, integrity, and compliance of data according to industry and company standards.

Your background might look something like:

• Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience (including data engineering).

• Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.

• Experience with data warehousing technologies such as Databricks and Snowflake, and expertise with ETL schedulers such as Fivetran, Airflow, Dagster, Prefect, or similar.

• Experience with distributed processing technologies and frameworks, such as Spark, Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see [OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement](https://cdn.openai.com/policies/eeo-policy-statement.pdf).

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information techn

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At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies.

We protect and accelerate any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks.

Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.

About Role

We are looking for experienced and highly motivated engineers to join our DATA Org and help build the future of data at Cloudflare. Our organisation is responsible for the entire data lifecycle - from ingestion and processing to storage and retrieval - powering the critical logs and analytics that provide our customers with real-time visibility into the health and performance of their online properties.

Our mission is to empower customers to leverage their data to drive better outcomes for their business. We build and maintain a suite of high-performance, scalable systems that handle more than a billion events in a second.

As an engineer in our organisation, you will have the opportunity to work on complex distributed systems challenges across different parts of our data stack.

Our Data Org is composed of several key teams, and you could contribute to any of the following areas:

• Data Delivery: You will build and operate our distributed data delivery pipeline, a high-throughput, low-latency system (primarily written in Go) responsible for ingesting, processing, and routing massive volumes of data from across Cloudflare's global network to multi-core destination.

• Analytical Database Platform: Contribute to our core analytical platform powered by ClickHouse. This team builds and maintains a high-performance, scalable database platform optimised for the immense analytical workloads generated by our products and services.

• Data Retrieval: Be responsible for building the customer-facing products that make data accessible and actionable. This includes developing our public GraphQL API, building robust log delivery solutions and integrations with customer destinations, and contributing to our alerting products, which empower users to configure and receive near real-time alerts based on the logs and metrics observed by our data platform.

Responsibilities

As a Software Engineer in our Data Organisation depending on the team you join, you will focus on a subset of the following areas:

• Design, develop, and maintain scalable and reliable distributed systems across the entire data lifecycle.

• Build and optimise key components of our high-throughput data delivery platform to ensure data integrity and low-latency delivery.

• Develop new and improve existing components for the Cloudflare Analytical Platform to extend functionality and performance.

• Scale, monitor, and maintain the performance of our large-scale database clusters to accommodate the growing volume of data.

• Develop and enhance our customer-facing GraphQL APIs, log delivery, and alerting solutions, focusing on performance, reliability, and user experience.

• Work to identify and remove bottlenecks across our data platforms, from streamlining data ingestion processes to optimising query performance.

• Collaborate with other teams across Cloudflare to understand their data needs and build solutions that empower them to make data-driven decisions.

• Collaborate with the ClickHouse open-source community to add new features and contribute to the upstream codebase.

• Participate in the development of the next generation of our data platforms, including researching and evaluating new technologies and approaches.

Key Qualifications

• 3+ years of experience working in software development covering distributed systems and databases.

• Strong programming skills (Golang is preferable), as well as a deep understanding of software development best practices and principles.

• Hands-on experience with modern observability stacks, including Prometheus, Grafana, and a strong understanding of handling high-cardinality metrics at scale.

• Strong knowledge of SQL and database internals, including experience with database design, optimisation, and performance tuning.

• A solid foundation in computer science, including algorithms, data structures, distributed systems, and concurrency.

• Strong analytical and problem-solving skills, with a willingness to debug, troubleshoot, and learn about complex problems at high scale.

• Ability to work collaboratively in a team environment and communicate effectively with other teams across Cloudflare.

• Experience with ClickHouse is a plus.

• Experience with data streaming technologies (e.g., Kafka, Flink) is a plus.

• Experience developing and scaling APIs, particularly GraphQL, is a plus.

• Experience with Infrastructure as Code tools like SALT or Terraform is a plus.

• Experience with Linux container technologies, such as Docker and Kubernetes, is a plus.

If you're passionate about building scalable and performant data platforms using cutting-edge technologies and want to work with a world-class team of engineers, then we want to hear from you!

Join us in our mission to help build a better internet for everyone!

This role requires flexibility to be on-call outside of standard working hours to address technical issues as needed.

What Makes Cloudflare Special?

We’re not just a highly ambitious, large-scale technology company. We’re a highly ambitious, large-scale technology company with a soul.

Fundamental to our mission to help build a better Internet is protecting the free and open Internet.

Project Galileo: Since 2014, we've equipped more than 2,400 journalism and civil society organisations in 111 countries with powerful tools to defend themselves against attacks that would otherwise censor their work, technology already used by Cloudflare’s enterprise customers--at no cost.

Athenian Project: In 2017, we created the Athenian Project to ensure that state and local governments have the highest level of protection and reliability for free, so that their constituents have access to election information and voter registration.

Since the project, we've provided services to more than 425 local government election websites in 33 states.

1.1.1.1: We released 1.1.1.1 to help fix the foundation of the Internet by building a faster, more secure and privacy-centric public DNS resolver. This is available publicly for everyone to use - it is the first consumer-focused service Cloudflare has ever released.

Here’s the deal - we don’t store client IP addresses never, ever. We will continue to abide by our privacy commitment and ensure that

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You will build the foundational capabilities that power our products used by research scientists, aerospace engineers, intelligence analysts, and economic forecasters, in countries around the world.

We're hiring engineers who are passionate about solving real-world problems and empowering both developers and end-users to work optimally.

If you’re motivated to develop reliable, performant, and scalable systems, and to design robust APIs and primitives, this role offers the opportunity to make a significant impact on our products and the people who use them.

As a Senior Backend Software Engineer - Infrastructure, you will:

• Build a performant search and indexing ecosystem for complex granularly permissioned data
• Contribute to open-source data processing libraries, integrating the latest innovations to achieve performance gains
• Build the distributed systems that power large scale compute workloads, orchestrating and efficiently scheduling hundreds of thousands of containers every hour
• Design architecture and opinionated APIs to keep application developers on the happy path
• Trace and performance observability in high scale distributed microservice architectures
• Build reliant, performant, and scalable systems for storage, auth, or asset serving to enable other product teams to build robust applications without deep domain expertise in the underlying systems
• Automate the deployment, management, and operations of complex distributed systems like Cassandra, Elasticsearch, Kafka, and more across different environments

We use different backend languages, including Java, Rust, and Go, and open-source technologies like Cassandra, ElasticSearch, Spark, Kafka, Kubernetes, Flink, and industry-standard build tooling, including Gradle and GitHub.

To succeed in this role, you will need to demonstrate:

• Demonstrated ability to collaborate and empathize with a variety of individuals
• Ability to learn new technology and concepts, even without in-depth experience
• Bias towards quality and thoughtful about edge cases (“anything that can go wrong will go wrong”); writes code that is defensive against all possibilities
• Leading solutions and APIs with users in mind while maintaining a high engineering bar

We require:

• 6+ years of experience designing, building, and operating scalable and reliable infrastructure systems in a production environment
• Engineering background in Computer Science, Mathematics, Software Engineering, Physics or similar field
• Strong coding skills with demonstrated proficiency in programming languages, such as Java, C++, Python, Rust, or similar languages
• Familiarity with storage and data processing systems, cloud infrastructure, and other technical tools
• Strong written and verbal communication skills and ability to iterate quickly with teammates, incorporating feedback and holding a high bar for quality

The estimated salary range for this position is $135,000 - $200,000/year.

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The role involves building a performant search and indexing ecosystem for complex granularly permissioned data, contributing to open-source data processing libraries, and designing architecture and opinionated APIs to keep application developers on the happy path.

As a member of the infrastructure team, you will work on building the foundational capabilities that power our products used by research scientists, aerospace engineers, intelligence analysts, and economic forecasters, in countries around the world.

We're hiring engineers who are passionate about solving real-world problems and empowering both developers and end-users to work optimally. If you’re motivated to develop reliable, performant, and scalable systems, and to design robust APIs and primitives, this role offers the opportunity to make a significant impact on our products and the people who use them.

Frontline Foundry Software Engineers may be offered the opportunity to Frontline, an exclusive program unlike any other. This unique, short-term assignment involves being embedded with customers, allowing you to work directly with users and gain firsthand insight into how our products are used and the challenges our customers face.

Some of our most successful products were built on the factory floor, addressing real-world problems for the world's most important institutions. These products were developed by some of our most successful product engineers, who began their careers in roles aligned with Frontline responsibilities, gaining a deep understanding of both our technology and our customers.

Core Responsibilities:

• Building a performant search and indexing ecosystem for complex granularly permissioned data
• Contributing to open-source data processing libraries, integrating the latest innovations to achieve performance gains
• Building the distributed systems that power large scale compute workloads, orchestrating and efficiently scheduling hundreds of thousands of containers every hour
• Designing architecture and opinionated APIs to keep application developers on the happy path
• Tracing and performance observability in high scale distributed microservice architectures
• Building reliant, performant, and scalable systems for storage, auth, or asset serving to enable other product teams to build robust applications without deep domain expertise in the underlying systems
• Automating the deployment, management, and operations of complex distributed systems like Cassandra, Elasticsearch, Kafka, and more across different environments

Technologies We Use:

• Different backend languages, including Java, Rust, and Go
• Open-source technologies like Cassandra, ElasticSearch, Spark, Kafka, Kubernetes, Flink
• Industry-standard build tooling, including Gradle and GitHub

What We Value:

• Demonstrated ability to collaborate and empathize with a variety of individuals. Able to iterate with users and non-technical stakeholders and understand how technical decisions impact them.
• Ability to learn new technology and concepts, even without in-depth experience. Experience developing and managing highly-available distributed systems is beneficial, but not required.
• Bias towards quality and thoughtful about edge cases (“anything that can go wrong will go wrong”); writes code that is defensive against all possibilities.
• Leading solutions and APIs with users in mind while maintaining a high engineering bar. Seeks to centralize and abstract complexity away from our users in order to expose simple, powerful APIs for consumers.
• Active UK Security clearance, or eligibility and willingness to obtain a UK Security clearance is beneficial, but not necessary.

What We Require:

• 6+ years of experience designing, building, and operating scalable and reliable infrastructure systems in a production environment
• Engineering background in Computer Science, Mathematics, Software Engineering, Physics or similar field.
• Strong coding skills with demonstrated proficiency in programming languages, such as Java, C++, Python, Rust, or similar languages.
• Familiarity with storage and data processing systems, cloud infrastructure, and other technical tools.
• Strong written and verbal communication skills and ability to iterate quickly with teammates, incorporating feedback and holding a high bar for quality.

Additional Information:

Life at Palantir

We want every Palantirian to achieve their best outcomes, that’s why we celebrate individuals’ strengths, skills, and interests, from your first interview to your longterm growth, rather than rely on traditional career ladders. Paying attention to the needs of our community enables us to optimize our opportunities to grow and helps ensure many pathways to success at Palantir.

Promoting health and well-being across all areas of Palantirians’ lives is just one of the ways we’re investing in our community. Learn more at Life at Palantir and note that our offerings may vary by region.

In keeping consistent with Palantir’s values and culture, we believe employees are “better together” and in-person work affords the opportunity for more creative outcomes. Therefore, we encourage employees to work from our offices to foster connectivity and innovation. Many teams do offer hybrid options (WFH a day or two a week), allowing our employees to strike

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Our mission is to democratize finance for all.

An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history.

If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact.

Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers.

We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Data Platform organization builds and operates the systems that power how data is stored, moved, and consumed across Robinhood.

This organization spans three core pillars: Storage (Postgres, DynamoDB, and caching systems), Streaming (real-time event infrastructure), and Data Lake (ingestion and compute systems built on Delta Lake).

Together, these platforms support transactional workloads, real-time data processing, and large-scale analytics that are critical to Robinhood’s products and operations.

The team owns the full lifecycle of data,from low-latency order path systems to near real-time and batch analytics,serving millions of users and internal teams across the company.

As a Senior Staff Software Engineer, you will serve as the technical lead across the Data Platform organization, shaping architecture and guiding execution across multiple teams.

You’ll work on complex distributed systems challenges such as database sharding and proxy architectures, real-time streaming and CDC systems, and large-scale data ingestion and compute platforms.

You’ll define and drive key technical bets, partner with engineering leaders to align platform capabilities with business needs, and lead 0→1 initiatives that introduce new capabilities across storage, streaming, and data systems.

This is a rare opportunity to influence multiple critical systems at once while raising the technical bar across an entire organization!

What you’ll do

Lead architectural direction across storage, streaming, and data lake platforms, connecting systems that handle transactional, real-time, and analytical workloads.

Design and guide implementation of distributed systems, including database sharding, proxy-based query routing, and real-time event processing pipelines.

Improve data freshness and latency by evolving streaming and ingestion systems toward near real-time processing goals.

Partner with engineering leaders and teams across Robinhood to define platform strategy, align roadmaps, and ensure systems meet reliability, scalability, and performance requirements.

Drive 0→1 initiatives that introduce new platform capabilities, including next-generation streaming, CDC, and data processing systems.

What you bring

Extensive experience building and scaling distributed systems, with deep expertise in at least two of the following areas: storage systems, streaming platforms, or data lake / large-scale data processing.

Strong understanding of database systems such as PostgreSQL and/or DynamoDB, including replication, sharding, and performance optimization.

Experience with streaming and event-driven architectures using technologies such as Kafka, Flink, or similar systems.

Familiarity with modern data platforms and compute engines such as Spark, Delta Lake, or equivalent large-scale data processing systems.

Proven ability to lead complex technical initiatives, define long-term architecture, and collaborate across multiple teams.

What we offer

Challenging, high-impact work to grow your career.

Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.

Best in class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.

Lifestyle wallet – a highly flexible benefits spending account for wellness, learning, and more.

Employer-paid life & disability insurance, fertility benefits, and mental health benefits.

Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!

Exceptional office experience with catered meals, events, and comfortable workspaces.

In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.

Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands.

The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones.

For other locations not listed, compensation can be discussed with your recruiter during the interview process.

Base Pay Range:

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)$264,000-$310,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)$264,000-$310,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)$264,000-$310,000 USD

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Core Responsibilities

• Building a performant search and indexing ecosystem for complex granularly permissioned data
• Contributing to open-source data processing libraries, integrating the latest innovations to achieve performance gains
• Building the distributed systems that power large scale compute workloads, orchestrating and efficiently scheduling hundreds of thousands of containers every hour
• Designing architecture and opinionated APIs to keep application developers on the happy path
• Tracing and performance observability in high scale distributed microservice architectures
• Building reliant, performant, and scalable systems for storage, auth, or asset serving to enable other product teams to build robust applications without deep domain expertise in the underlying systems
• Automating the deployment, management, and operations of complex distributed systems like Cassandra, Elasticsearch, Kafka, and more across different environments

Technologies We Use

• Different backend languages, including Java, Rust, and Go
• Open-source technologies like Cassandra, ElasticSearch, Spark, Kafka, Kubernetes, Flink
• Industry-standard build tooling, including Gradle and GitHub

What We Value

• Demonstrated ability to collaborate and empathize with a variety of individuals
• Ability to learn new technology and concepts, even without in-depth experience
• Bias towards quality and thoughtful about edge cases
• Builds solutions and APIs with users in mind while maintaining a high engineering bar

What We Require

• Engineering background in Computer Science, Mathematics, Software Engineering, Physics or similar field
• Strong coding skills with demonstrated proficiency in programming languages, such as Java, C++, Python, Rust, or similar languages
• Familiarity with storage and data processing systems, cloud infrastructure, and other technical tools
• Strong written and verbal communication skills and ability to iterate quickly with teammates, incorporating feedback and holding a high bar for quality

Additional Information

The estimated salary range for this position is estimated to be $135,000 - $200,000/year. Total compensation for this position may also include Restricted Stock units, sign-on bonus and other potential future incentives.

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Our Software Engineers are involved throughout the product lifecycle, from idea generation, design, prototyping, and production delivery. We encourage movement across teams to share context, skills, and experience, so you'll learn about many different technologies and aspects of each product.

As a Software Engineer on infrastructure, you'll contribute high-quality code to underpin Palantir Foundry and Gotham with performant, secure, and scalable building blocks, enabling products deployed to the most important institutions in the public and private sector.

We're hiring engineers who are passionate about solving real-world problems and empowering both developers and end-users to work optimally. If you're motivated to develop reliable, performant, and scalable systems, and to design robust APIs and primitives, this role offers the opportunity to make a significant impact on our products and the people who use them.

Core Responsibilities

• Building a performant search and indexing ecosystem for complex granularly permissioned data
• Contributing to open-source data processing libraries, integrating the latest innovations to achieve performance gains
• Building the distributed systems that power large scale compute workloads, orchestrating and efficiently scheduling hundreds of thousands of containers every hour
• Designing architecture and opinionated APIs to keep application developers on the happy path
• Tracing and performance observability in high scale distributed microservice architectures
• Building reliant, performant, and scalable systems for storage, auth, or asset serving to enable other product teams to build robust applications without deep domain expertise in the underlying systems
• Automating the deployment, management, and operations of complex distributed systems like Cassandra, Elasticsearch, Kafka, and more across different environments

Technologies We Use

• Different backend languages, including Java, Rust, and Go
• Open-source technologies like Cassandra, ElasticSearch, Spark, Kafka, Kubernetes, Flink
• Industry-standard build tooling, including Gradle and GitHub

What We Value

• Demonstrated ability to collaborate and empathise with a variety of individuals. Able to iterate with users and non-technical stakeholders and understand how technical decisions impact them.
• Ability to learn new technology and concepts, even without in-depth experience. Experience developing and managing highly-available distributed systems is beneficial, but not required.
• Bias towards quality and thoughtful about edge cases (“anything that can go wrong will go wrong”); writes code that is defensive against all possibilities.
• Builds solutions and APIs with users in mind while maintaining a high engineering bar. Seeks to centralise and abstract complexity away from our users in order to expose simple, powerful APIs for consumers.
• Active UK Security clearance, or eligibility and willingness to obtain a UK Security clearance is beneficial, but not necessary.

What We Require

• Engineering background in Computer Science, Mathematics, Software Engineering, Physics or similar field.
• Strong coding skills with demonstrated proficiency in programming languages, such as Java, C++, Python, Rust, or similar languages.
• Familiarity with storage and data processing systems, cloud infrastructure, and other technical tools.
• Strong written and verbal communication skills and ability to iterate quickly with teammates, incorporating feedback and holding a high bar for quality.

Additional Information

Life at Palantir

We want every Palantirian to achieve their best outcomes, that’s why we celebrate individuals’ strengths, skills, and interests, from your first interview to your longterm growth, rather than rely on traditional career ladders. Paying attention to the needs of our community enables us to optimize our opportunities to grow and helps ensure many pathways to success at Palantir.

Promoting health and well-being across all areas of Palantirians’ lives is just one of the ways we’re investing in our community. Learn more at Life at Palantir and note that our offerings may vary by region.

In keeping consistent with Palantir’s values and culture, we believe employees are “better together” and in-person work affords the opportunity for more creative outcomes. Therefore, we encourage employees to work from our offices to foster connectivity and innovation. Many teams do offer hybrid options (WFH a day or two a week), allowing our employees to strike the right trade-off for their personal productivity. Based on business need, there are a few roles that allow for “Remote” work on an exceptional basis. If you are

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As a Software Engineer on infrastructure working on our Foundry platform, you'll collaborate closely with technical and non-technical teammates to understand our customers' problems and build products that solve them. You'll work autonomously and make decisions independently, within a community that will support and challenge you as you grow and develop, becoming a strong technical contributor and engineering leader.

Some of the key responsibilities of this role include:

• Building a performant search and indexing ecosystem for complex granularly permissioned data
• Contributing to open-source data processing libraries, integrating the latest innovations to achieve performance gains
• Building the distributed systems that power large scale compute workloads, orchestrating and efficiently scheduling hundreds of thousands of containers every hour
• Designing architecture and opinionated APIs to keep application developers on the happy path
• Tracing and performance observability in high scale distributed microservice architectures
• Building reliant, performant, and scalable systems for storage, auth, or asset serving to enable other product teams to build robust applications without deep domain expertise in the underlying systems
• Automating the deployment, management, and operations of complex distributed systems like Cassandra, Elasticsearch, Kafka, and more across different environments

We're looking for engineers who are passionate about solving real-world problems and empowering both developers and end-users to work optimally. If you're motivated to develop reliable, performant, and scalable systems, and to design robust APIs and primitives, this role offers the opportunity to make a significant impact on our products and the people who use them.

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The Data Platform team at xAI builds and operates the infrastructure responsible for all large-scale data transport and processing across the company.

As a software engineer on the Data Platform team, you will design, build, and operate the distributed systems powering X's data movement and compute.

Responsibilities

• Design and implement high-throughput, low-latency data ingestion and transport systems.
• Scale and optimise multi-tenant Kafka infrastructure supporting real-time workloads.
• Extend and tune Spark, Flink, and Trino for demanding production pipelines.
• Build interfaces, APIs, and pipelines enabling teams to query, process, and move data at petabyte scale.
• Debug and optimise distributed systems, with a focus on reliability and performance under load.
• Collaborate with ML, product, and infrastructure teams to unblock critical data workflows.

Basic Qualifications

• Proven expertise in distributed systems, stream processing, or large-scale data platforms.
• Proficiency in Rust, Go, Scala or similar systems languages.
• Hands-on experience with Kafka, Flink, Spark, Trino, or Hadoop in production.
• Strong debugging, profiling, and performance optimisation skills.
• Track record of shipping and maintaining critical infrastructure.
• Comfortable working in fast-moving, high-stakes environments with minimal guardrails.

Compensation and Benefits

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at X, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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You will be driving critical workstreams for Stripe's topmost priorities around delivering high quality, materialized datasets Stripe products and AI agents.

Key responsibilities include:

• Delivering infrastructure and services that scale to our users' needs with an eye on reliability and efficiency
• Leading and managing a team of talented engineers on the team, providing mentorship, guidance, and support to ensure their success
• Working with high-visibility teams and their stakeholders to support the Infrastructure's key engineering initiatives
• Understanding user needs and pain points to prioritize engineering work and deliver high quality solutions that meet user needs
• Driving the execution of projects, overseeing the entire development lifecycle from planning to delivery, while maintaining high standards of quality and timely completion

You will also provide hands-on technical leadership (architecture/design, vision/direction/requirements setting, and incident response processes) for your reports, work with leaders across the company to create and drive toward the longer term vision of Stripe's Data Transformation roadmap, and foster a collaborative and inclusive work environment, promoting innovation, knowledge sharing, and continuous improvement within the team.

We're looking for someone who has 1-3 years of experience managing teams that shipped and operated data pipelines and critical distributed system infrastructure, successfully recruited and built great teams, and works effectively cross-functionally and is able to think rigorously, communicate effectively, and make or coordinate hard decisions and trade-offs.

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As a software engineer on the Data Platform team, you will design, build, and operate the distributed systems powering X's data movement and compute. You will take ownership of infrastructure components that process trillions of events daily, driving the scalability, performance, and reliability of the systems that power product and ML workloads across the company.

Responsibilities

• Design and implement high-throughput, low-latency data ingestion and transport systems.
• Scale and optimize multi-tenant Kafka infrastructure supporting real-time workloads.
• Extend and tune Spark, Flink, and Trino for demanding production pipelines.
• Build interfaces, APIs, and pipelines enabling teams to query, process, and move data at petabyte scale.
• Debug and optimize distributed systems, with a focus on reliability and performance under load.
• Collaborate with ML, product, and infrastructure teams to unblock critical data workflows.

Basic Qualifications

• Proven expertise in distributed systems, stream processing, or large-scale data platforms.
• Proficiency in Rust, Go, Scala or similar systems languages.
• Hands-on experience with Kafka, Flink, Spark, Trino, or Hadoop in production.
• Strong debugging, profiling, and performance optimization skills.
• Track record of shipping and maintaining critical infrastructure.
• Comfortable working in fast-moving, high-stakes environments with minimal guardrails.

Compensation and Benefits

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at X, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

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Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $185K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the Team

Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows.

About the Role

This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale.

You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation.

Responsibilities

• Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security

• Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient

• Accelerate company productivity by empowering your fellow engineers & teammates with excellent data tooling and systems

• Collaborate with product, research and analytics teams to build the technical foundations capabilities that unlock new features and experiences

• Own the reliability of the systems you build, including participation in an on-call rotation for critical incidents

Requirements

• 4+ years in data infrastructure engineering OR

• 4+ years in infrastructure engineering with a strong interest in data

• Take pride in building and operating scalable, reliable, secure systems

• Are comfortable with ambiguity and rapid change

• Have an intrinsic desire to learn and fill in missing skills, and an equally strong talent for sharing learnings clearly and concisely with others

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of human diversity.

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Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $230K – $385K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

Benefits

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

About the team

The Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses.

We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth.

About the role

We're seeking a Data Engineer to take the lead in building our data pipelines and core tables for OpenAI. These pipelines are crucial for powering analyses, safety systems that guide business decisions, product growth, and prevent bad actors. If you're passionate about working with data and are eager to create solutions with significant impact, we'd love to hear from you. This role also provides the opportunity to collaborate closely with the researchers behind ChatGPT and help them train new models to deliver to users. As we continue our rapid growth, we value data-driven insights, and your contributions will play a pivotal role in our trajectory. Join us in shaping the future of OpenAI!

In this role, you will:

• Design, build and manage our data pipelines, ensuring all user event data is seamlessly integrated into our data warehouse.

• Develop canonical datasets to track key product metrics including user growth, engagement, and revenue.

• Work collaboratively with various teams, including, Infrastructure, Data Science, Product, Marketing, Finance, and Research to understand their data needs and provide solutions.

• Implement robust and fault-tolerant systems for data ingestion and processing.

• Participate in data architecture and engineering decisions, bringing your strong experience and knowledge to bear.

• Ensure the security, integrity, and compliance of data according to industry and company standards.

You might thrive in this role if you:

• Have 3+ years of experience as a data engineer and 8+ years of any software engineering experience(including data engineering).

• Proficiency in at least one programming language commonly used within Data Engineering, such as Python, Scala, or Java.

• Experience with distributed processing technologies and frameworks, such as Hadoop, Flink and distributed storage systems (e.g., HDFS, S3).

• Expertise with any of ETL schedulers such as Airflow, Dagster, Prefect or similar frameworks.

• Solid understanding of Spark and ability to write, debug and optimize Spark code.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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