About the Role We are at a pivotal scaling point where our data ambitions have outpaced our current setup, and we need a Data Engineer to architect the professional-grade foundations of our platform.
\nThis role exists to bridge the gap between "getting data" and "engineering data," moving us from manual syncs to a fully automated ecosystem. By building custom pipelines and implementing a robust orchestration layer, you will directly enable our Operations teams and leadership to transition from basic reporting to sophisticated, AI-ready data products.
\nYour primary focus will be on Infrastructure-as-Code, orchestration, and building a resilient "plumbing" system that serves as the backbone for our entire Product and GTM strategy.
\nYour 12-Month Journey During the first 3 months: you will learn about our existing stack (GCP, BigQuery, Airbyte, dbt) and understand the current pain points in our data flow. You will identify and execute "low-hanging fruit" improvements to our product usage analytics, providing immediate value to the Product and GTM teams. You’ll begin designing the blueprint for our custom data pipelines and the migration strategy for moving our infrastructure into Terraform.
\nWithin 6 months: You will have deployed our new orchestration layer (e.g., Airflow or Dagster) and successfully transitioned our first set of custom pipelines to production. Collaborating with the Analytics Engineer, you will enable a unified view of our customer journey by successfully merging product usage data with CRM and billing data. At this point, a significant portion of our data infrastructure will be defined as code, reducing manual overhead and increasing deployment reliability.
\nAfter 1 year: you will take full strategic ownership of the data platform and its long-term architecture. You will act as the go-to technical expert for the leadership team, advising on the scalability of new data-driven features. You will lay the groundwork for AI and Machine Learning initiatives by ensuring our data warehouse has the right quality controls, governance, and low-latency access patterns in place.
\nWhat You’ll Be Doing Architect Scalable Infrastructure-as-Code: Take our existing foundations to the next level by migrating all GCP and BigQuery resources into Terraform. You will establish automated CI/CD patterns to ensure our entire data environment is reproducible, version-controlled, and enterprise-ready.
\nDeploy State-of-the-Art Pipelines: Design, deploy, and operate high-quality production ELT pipelines. You will implement a modern orchestration layer (e.g., Airflow or Dagster) to build custom Python-based integrations while maintaining and optimizing our existing syncs.
\nChampion Data Quality & Performance: Act as the guardian of our data platform. You will implement rigorous testing and monitoring protocols to ensure data is accurate and timely. You will proactively identify BigQuery bottlenecks, optimizing query performance and resource utilization.
\nTechnical Roadmap & Ownership: scope and architect end-to-end data flows from production source to warehouse. Manage your own technical backlog, prioritizing infrastructure stability over technical debt. You will ensure platform security and SOC2 compliance through PII masking, data contracts, and robust access controls.
\nCollaboration: You will work in a tight loop with the Analytics Engineer to turn raw data into actionable products. You will partner daily with DataOps and RevOps to understand business requirements, with occasional strategic syncs with DevOps and R&D to align on production schema changes and global infrastructure standards.
\nWhat You Bring Solid experience in Data Engineering, with a track record of building and evolving data ingestion infrastructure in cloud environments. The Modern Data Stack: Familiarity with dbt and Airbyte/Fivetran. You understand how these tools fit into a broader ecosystem. Expertise in BigQuery (partitioning, clustering, IAM) and the broader GCP ecosystem; Infrastructure-as-Code (Terraform). Hands-on experience with Airflow, Dagster, or similar orchestration tools. You know how to design DAGs that are resilient and easy to debug. DevOps practices in the data context: familiarity with CI/CD best practices as they apply to data (data testing, automated deployments). Programming: Expert-level Python and advanced SQL. You are comfortable writing clean, testable, and modular code. Comfortable in a fast-paced environment Project management skills: capable of managing stakeholders, explaining complicated technical trade-offs to non-technical users, and taking care of own project scoping and backlog management. Fluency in English, both written and spoken, at a minimum C1 level
\nWhat We Offer Flexibility to work from home in the Netherlands and from our beautiful canal-side office in Amsterdam A chance to be part of and shape one of the most ambitious scale-ups in Europe Work in a diverse and multicultural team €1,500 annual training budget plus internal training Pension plan, travel reimbursement, and wellness perks 28 paid holiday days + 2 additional days to relax in 2026 Work from anywhere for 4 weeks/year An inclusive and international work environment with a whole lot of fun thrown in! Apple MacBook and tools €200 Home Office budget
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_21f5f6c3-734","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Tellent","sameAs":"https://careers.tellent.com","logo":"https://logos.yubhub.co/careers.tellent.com.png"},"x-apply-url":"https://careers.tellent.com/o/data-engineer","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"EUR 70000–90000 / year","x-skills-required":["Data Engineering","Cloud environments","dbt","Airbyte/Fivetran","BigQuery","GCP ecosystem","Infrastructure-as-Code","Terraform","Airflow","Dagster","Python","SQL","CI/CD best practices","DevOps practices"],"x-skills-preferred":[],"datePosted":"2026-04-18T22:12:06.548Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Amsterdam"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Data Engineering, Cloud environments, dbt, Airbyte/Fivetran, BigQuery, GCP ecosystem, Infrastructure-as-Code, Terraform, Airflow, Dagster, Python, SQL, CI/CD best practices, DevOps practices","baseSalary":{"@type":"MonetaryAmount","currency":"EUR","value":{"@type":"QuantitativeValue","minValue":70000,"maxValue":90000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_09a4d1ce-cde"},"title":"Data Engineer","description":"We are looking for an experienced Data Engineer to partner with our Data Science and Data Infrastructure teams to own and scale our data pipelines. You'll also work closely with stakeholders across business teams including sales, marketing, and finance to ensure that the data they need arrives promptly and reliably.
\nAs a Data Engineer at Figma, you will be responsible for building and maintaining scalable data pipelines that connect various cloud data sources. You will develop a deep understanding of Figma's core data models and optimize data pipelines for scale. You will partner with the Data Science and Data Infrastructure teams to build new foundational data sets that are trusted, well understood, and enable self-service.
\nYou will work with a wide range of cross-functional stakeholders to derive requirements and architect shared datasets; ability to document, simplify and explain complex problems to different types of audiences. You will establish best practices for the development of specialized data sets for analytics and modeling.
\nWe'd love to hear from you if you have:
\nWhile not required, it's an added plus if you also have:
\nAt Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you're excited about this role but your past experience doesn't align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_09a4d1ce-cde","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Figma","sameAs":"https://www.figma.com/","logo":"https://logos.yubhub.co/figma.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/figma/jobs/5220003004","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$140,000-$348,000 USD","x-skills-required":["SQL","Python","Snowflake","dbt","Dagster","ETL/reverse ETL tools"],"x-skills-preferred":["data modeling methodologies","business systems such as Salesforce, Customer IO, Stripe, NetSuite"],"datePosted":"2026-04-18T15:51:04.727Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA • New York, NY • United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"SQL, Python, Snowflake, dbt, Dagster, ETL/reverse ETL tools, data modeling methodologies, business systems such as Salesforce, Customer IO, Stripe, NetSuite","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":140000,"maxValue":348000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_01845b18-90a"},"title":"Tech Lead (CI & Test Data Platform)","description":"At Trunk, our mission is to help teams create high-quality software quickly. We've helped engineerings teams at Google X, Zillow, and Brex to understand why their builds fail, which tests are flaky, and how to ship code faster without sacrificing reliability. AI has made writing code 10x faster, but shipping is still painfully slow. The bottleneck has shifted downstream - to merge conflicts, flaky tests, inconsistent code quality, and dozens of other frictions that drain productivity and morale. Engineering teams that can stay focused on designing, implementing, and delivering software will build magical, high-quality projects - and they'll be happier doing it. We're building a CI Reliability Platform that empowers teams to land code faster and develop happier.
\nOur founders launched Trunk in 2021 after designing, delivering, and scaling software at Uber, Google, YouTube, and Microsoft. We raised a $25M Series A led by Initialized Capital (Garry Tan) and a16z (Peter Levine), with investments from Haystack Ventures, Garage VC, and the founders of GitHub (Tom Preston-Werner), Apollo GraphQL (Geoff Schmidt), Algolia (Nicolas Dessaigne), and Peopl.ai (Oleg Rogynsky).
\nCI pipelines are black boxes. Engineers waste hours debugging failures that turn out to be flaky tests or infrastructure noise. Trunk makes this visible: what failed, why, and whether it's worth fixing.
\nThe next wave is agentic. AI tools today hit a wall when code leaves the local environment. We're building the data layer that lets AI agents actually reason about CI: diagnosing failures, suggesting fixes, and eventually shipping code autonomously.
\nWe're looking for a Tech Lead to own the data platform that powers Trunk's flaky test detection and CI analytics products. You'll design and build the systems that ingest millions of test runs per hour, surface actionable insights, and lay the foundation for AI-driven CI workflows.
\nWe're at an inflection point. The scale challenges are real and growing. The AI/agentic future of development tooling is taking shape, and we're building the data infrastructure that makes it possible. If you want to work on hard systems problems with direct customer impact, this is the role.
\nAs a Tech Lead, you will:
\nWe're looking for someone with:
\nYou're a good fit if:
\nOur tech stack includes:
\nWe offer:
\nThe salary and equity range for this role are: $200-$245K and .3-.5%.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_01845b18-90a","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Trunk","sameAs":"https://trunk.io","logo":"https://logos.yubhub.co/trunk.io.png"},"x-apply-url":"https://jobs.lever.co/trunkio/32921dae-d3b1-4771-bb09-cac8a3b14d0c","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$200-$245K","x-skills-required":["Rust","Python","Typescript","PostgreSQL","ClickHouse","AWS","Kubernetes","Dagster"],"x-skills-preferred":[],"datePosted":"2026-04-17T13:07:07.005Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Rust, Python, Typescript, PostgreSQL, ClickHouse, AWS, Kubernetes, Dagster","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":245000,"maxValue":245000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d3dad1eb-2a2"},"title":"Senior Software Engineer (Platform)","description":"At Trunk, our mission is to help teams create high-quality software quickly. We've helped engineerings teams at Google X, Zillow, and Brex to understand why their builds fail, which tests are flaky, and how to ship code faster without sacrificing reliability.
\nThe bottleneck has shifted downstream - to merge conflicts, flaky tests, inconsistent code quality, and dozens of other frictions that drain productivity and morale. Engineering teams that can stay focused on designing, implementing, and delivering software will build magical, high-quality projects - and they'll be happier doing it.
\nWe're building a CI Reliability Platform that empowers teams to land code faster and develop happier.
\nWe are looking for a motivated and experienced Senior Software Engineer to join our Platform/Data Engineering team. In this role, you will be responsible for developing and optimizing data ingestion pipelines that can handle vast amounts of real-time and batch data from various sources.
\nYour focus will be on designing systems that are scalable, reliable, and performant, as well as ensuring the proper integration of data across our entire ecosystem.
\nResponsibilities
\nRequirements
\nTech Stack
\nBenefits
\nThe salary and equity range for this role are: $170K - $210K and .15% - .35%.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_d3dad1eb-2a2","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Trunk","sameAs":"https://trunk.io","logo":"https://logos.yubhub.co/trunk.io.png"},"x-apply-url":"https://jobs.lever.co/trunkio/43b778ae-e2b0-472c-8316-a079da4e54da","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$170K - $210K","x-skills-required":["databases","distributed systems","service-oriented architectures","data infrastructure","typescript","react","next.js","aws","node","python","polars","dagster","github actions"],"x-skills-preferred":[],"datePosted":"2026-04-17T13:06:44.831Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"databases, distributed systems, service-oriented architectures, data infrastructure, typescript, react, next.js, aws, node, python, polars, dagster, github actions","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":170000,"maxValue":210000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_e503559e-cf7"},"title":"Senior Machine Learning Engineer","description":"Job Title: Senior Machine Learning Engineer
\nJob Description:
\nBefore 1965, it was extremely difficult and time-consuming to analyze complicated signals, like radio or images. You could solve it, but you had to throw a ton of compute at it. That all changed with the invention of the Fast Fourier transform, which could efficiently break that signal down into the frequencies that are a part of it.
\nThe Risk Onboarding team is working on efficiently reviewing customers’ applications without compromising on quality. We are the front line of defense for preventing money laundering and financial crimes, building systems to verify that someone is who they say they are and that we are allowed to do business with them.
\nAbout Us:
\nAt Mercury, we craft an exceptional banking experience for startups. Our team is focused on ensuring our products create a safe environment that meets the needs of our customers, administrators, and regulators.
\nJob Responsibilities:
\nAs part of this role, you will:
\nIdeal Candidate:
\nThe ideal candidate for the role has:
\nTotal Rewards Package:
\nThe total rewards package at Mercury includes base salary, equity (stock options/RSUs), and benefits. Our salary and equity ranges are highly competitive within the SaaS and fintech industry and are updated regularly using the most reliable compensation survey data for our industry. New hire offers are made based on a candidate’s experience, expertise, geographic location, and internal pay equity relative to peers.
\nSalary Range:
\nOur target new hire base salary ranges for this role are the following:
\nDiversity & Belonging:
\nMercury values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Mercury are considered without regard to race, color, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, sexual orientation, or any other legally protected characteristic.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_e503559e-cf7","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Mercury","sameAs":"https://www.mercury.com/","logo":"https://logos.yubhub.co/mercury.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/mercury/jobs/5639559004","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$200,700 - $250,900 (US) | CAD 189,700 - 237,100 (Canada)","x-skills-required":["Snowflake","dbt","Fivetran","Airbyte","Dagster","Airflow","SQL","Python","OLAP / OLTP data modelling and architecture","Redis","dynamoDB","Kinesis","Kafka","Redpanda","FastAPI","Flask","Production ML Service experience","Haskell","React","TypeScript"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:45:16.566Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco, CA, New York, NY, Portland, OR, or Remote within Canada or United States"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Finance","skills":"Snowflake, dbt, Fivetran, Airbyte, Dagster, Airflow, SQL, Python, OLAP / OLTP data modelling and architecture, Redis, dynamoDB, Kinesis, Kafka, Redpanda, FastAPI, Flask, Production ML Service experience, Haskell, React, TypeScript","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":189700,"maxValue":250900,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_f0f321c2-15d"},"title":"Data Platform Engineer","description":"At Anchorage Digital, we are building the world's most advanced digital asset platform for institutions to participate in crypto. Join the Data Platform team and build the Trusted Data Platform that powers Anchorage's transition to Data 3.0.
\nYou'll help shape the unified orchestration foundation, collaborate on governance-as-code patterns, and contribute to self-service frameworks that make quality and compliance automatic. We're moving from manual spreadsheets and theoretical architectures to automated control planes where every dataset is trusted, monitored, and traceable by default.
\nTechnical Skills:
\nComplexity and Impact of Work:
\nOrganizational Knowledge:
\nCommunication and Influence:
\nYou may be a fit for this role if you:
\nAlthough not a requirement, bonus points if:
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_f0f321c2-15d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anchorage Digital","sameAs":"https://www.anchorage.co/","logo":"https://logos.yubhub.co/anchorage.co.png"},"x-apply-url":"https://jobs.lever.co/anchorage/8a325cd5-ef99-4f1e-bba8-7bb1fca64f12","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["dbt","SQL","Airflow","Dagster","Prefect","BigQuery","Snowflake","Redshift"],"x-skills-preferred":["Metadata and catalog experience","Data observability tools","Infrastructure as code"],"datePosted":"2026-04-17T12:24:40.602Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"dbt, SQL, Airflow, Dagster, Prefect, BigQuery, Snowflake, Redshift, Metadata and catalog experience, Data observability tools, Infrastructure as code"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_72eaaa6e-3c0"},"title":"Founding Engineer - Reporting & Statements","description":"Join us as a founding engineer on our Reporting & Statements team. You'll design the systems that power every financial report and statement we deliver from monthly reports to daily statements to custom client requests. We're building automated frameworks that guarantee accuracy and consistency for every number we send to clients.
\nTechnical Skills:
\nComplexity and Impact of Work:
\nOrganizational Knowledge:
\nCommunication and Influence:
\nYou may be a fit for this role if you:
\nAlthough not a requirement, bonus points if:
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_72eaaa6e-3c0","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anchorage Digital","sameAs":"https://www.anchorage.co/","logo":"https://logos.yubhub.co/anchorage.co.png"},"x-apply-url":"https://jobs.lever.co/anchorage/5bcfc8f2-5f26-4f72-8ca7-f4b20ee7f7db","x-work-arrangement":"remote","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Python","SQL","BigQuery","Airflow","Dagster","Pandas","Polars","Arrow"],"x-skills-preferred":[],"datePosted":"2026-04-17T12:23:54.465Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York City"}},"jobLocationType":"TELECOMMUTE","employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, SQL, BigQuery, Airflow, Dagster, Pandas, Polars, Arrow"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_b1d4c773-5c5"},"title":"Analytics Engineer, Finance","description":"Compensation
\nThe 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.
\nAbout the Team
\nThe Finance Data team is embedded within the CFO Org and is responsible for building internal data products that scale analytics across business teams and drive efficiencies in our daily operations. This team provides technical guidance on high-impact, scalable projects across Finance, and is the subject-matter expert in financial and transactional data that supports our Finance day-to-day operations.
\nAbout the Role
\nAs an Analytics Engineer, you will be setting the foundation to scale analytics across our business functions and impart best data practices for a rapidly growing organization. We aspire to build the Finance team of the future.
\nIn addition, you will work collaboratively with key stakeholders in Finance and other business teams to understand their pain points and take the lead in proposing viable, future-proof solutions to resolve them. You will also autonomously lead your own projects that deliver business impact and help cultivate a mature data culture among Finance teams.
\nWe are looking for a seasoned engineer who has a proven track record of owning the entire data stack at high transaction volume companies, managing business critical ETL pipelines consumed by non-technical teams. As a generalist “fixer”, you may be deployed across several different Finance domains (e.g. Tax datamart, ERP migration, Procurement automation). For this role we need someone who excels in dynamic environments, adapts quickly to changing needs, and confidently navigates ambiguous or evolving requirements. If you're energized by solving technical problems without a playbook and comfortable wearing multiple hats, this role is for you! To clarify, you will not be responsible for training ML models and neither would we describe this role as ‘product analytics’.
\nThis role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
\nIn this role, you will:
\nYou might thrive in this role if you have:
\nYou could be an especially great fit if you have:
\nAbout OpenAI
\nOpenAI 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.
\nWe 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.
\nFor additional information, please see [OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement](https://cdn.openai.com/policies/eeo-policy-statement.pdf).
\nBackground 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
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_b1d4c773-5c5","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/7cd50a19-65f2-4a52-89a2-512130e58c5c","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"Full time","x-salary-range":"$198K – $260K • Offers Equity","x-skills-required":["SQL","Python","R","S3","Trino","Hive","Spark","Airflow","Dagster","GitHub","Stash","Tableau","Looker"],"x-skills-preferred":["React","TypeScript","ReTool","Streamlit","Web development"],"datePosted":"2026-03-08T22:16:37.388Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"SQL, Python, R, S3, Trino, Hive, Spark, Airflow, Dagster, GitHub, Stash, Tableau, Looker, React, TypeScript, ReTool, Streamlit, Web development","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":198000,"maxValue":260000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_d6450ee6-847"},"title":"Data Infrastructure Engineer","description":"About the Role
\nCursor ships daily. Every release leaves signals behind: telemetry, prompts, completions, agent runs, sessions. Those signals power model improvement, evals, and experimentation. Data infrastructure is what turns them into something teams can trust.
\nA lot of systems here started simple so we could move fast. Over time, the constraints change and the “good enough” version becomes the bottleneck. This role owns the full ladder: patch what should be patched, redesign what should be redesigned, ship the replacement, and operate it.
\nPrivacy guarantees are part of correctness. What we can retain and use depends on Privacy Mode and org configuration, and getting that wrong breaks a product promise. We choose work by business impact: what blocks product and model teams today, and what will block them next month.
\nSample projects include...
\nWhat we're looking for
\nWe’re looking for someone who has built real systems at scale and cares about correctness, cost, and ergonomics.
\nStrong signals include:
\nNice to have
\nWe're in-person with cozy offices in North Beach, San Francisco and Manhattan, New York, replete with well-stocked libraries.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_d6450ee6-847","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Cursor","sameAs":"https://cursor.com","logo":"https://logos.yubhub.co/cursor.com.png"},"x-apply-url":"https://cursor.com/careers/software-engineer-data-infrastructure","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":null,"x-skills-required":["Spark","Ray Data","data pipelines","storage systems","debugging performance issues","data modeling","long-term maintainability"],"x-skills-preferred":["ClickHouse","dbt","Dagster"],"datePosted":"2026-03-08T00:17:58.290Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Spark, Ray Data, data pipelines, storage systems, debugging performance issues, data modeling, long-term maintainability, ClickHouse, dbt, Dagster"},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_c873a489-0dc"},"title":"Data Engineer, Analytics","description":"Data Engineer, Analytics
\nLocation
\nSan Francisco
\nEmployment Type
\nFull time
\nDepartment
\nApplied AI
\nCompensation
\nThe 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.
\nBenefits
\nAbout the team
\nThe Applied team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses.
\nWe 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.
\nAbout the role
\nWe'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!
\nIn this role, you will:
\nYou might thrive in this role if you:
\nAbout OpenAI
\nOpenAI 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.
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_c873a489-0dc","directApply":true,"hiringOrganization":{"@type":"Organization","name":"OpenAI","sameAs":"https://jobs.ashbyhq.com","logo":"https://logos.yubhub.co/openai.com.png"},"x-apply-url":"https://jobs.ashbyhq.com/openai/fc5bbc77-a30c-4e7a-9acc-8a2e748545b4","x-work-arrangement":"onsite","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$230K – $385K • Offers Equity","x-skills-required":["Python","Scala","Java","Hadoop","Flink","HDFS","S3","Airflow","Dagster","Prefect","Spark"],"x-skills-preferred":[],"datePosted":"2026-03-06T18:20:01.101Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Francisco"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"Python, Scala, Java, Hadoop, Flink, HDFS, S3, Airflow, Dagster, Prefect, Spark","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":230000,"maxValue":385000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_2902359a-64d"},"title":"Member of Technical Staff, Infrastructure Data & Analytics","description":"Summary
\nMicrosoft AI are looking for a talented Member of Technical Staff, Infrastructure Data & Analytics to join their MAI SuperIntelligence Team. This role sits at the heart of strategic decision-making, turning raw telemetry into trusted, decision-quality insights on utilization, capacity, readiness, and efficiency. You'll work directly with leadership to shape the company's direction in the Superintelligence space.
\nAbout the Role
\nAs a Member of Technical Staff, Infrastructure Data & Analytics, you will act as the technical lead and owner for infrastructure analytics across compute, storage, and networking. You will design and build durable, scalable data pipelines that ingest telemetry from clusters, schedulers, health systems, and capacity trackers into Data Warehouse. You will define and standardize core metrics and semantics (e.g., utilization, occupancy, MFU, goodput, capacity readiness, delivery-to-production). You will architect and maintain self-service dashboards and APIs for fleet, cluster, and squad-level visibility. You will partner closely with stakeholders across Supercomputing Infra, Researchers, Strategy and Executives to ensure metrics reflect operational and business reality.
\nAccountabilities
\nThe Candidate we're looking for
\nExperience:
\nTechnical skills:
\nPersonal attributes:
\nBenefits
\nXML job scraping automation by YubHub
","url":"https://yubhub.co/jobs/job_2902359a-64d","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Microsoft AI","sameAs":"https://microsoft.ai","logo":"https://logos.yubhub.co/microsoft.ai.png"},"x-apply-url":"https://microsoft.ai/job/member-of-technical-staff-infrastructure-data-analytics-mai-superintelligence-team/","x-work-arrangement":"onsite","x-experience-level":"staff","x-job-type":"full-time","x-salary-range":"USD $139,900 – $274,800 per year","x-skills-required":["data engineering","analytics","data science","distributed data processing frameworks","large-scale data systems"],"x-skills-preferred":["ETL orchestration frameworks","Airflow","Dagster"],"datePosted":"2026-03-06T07:29:22.881Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Multiple Locations, United States"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Technology","skills":"data engineering, analytics, data science, distributed data processing frameworks, large-scale data systems, ETL orchestration frameworks, Airflow, Dagster","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":139900,"maxValue":274800,"unitText":"YEAR"}}}]}