You'll architect and implement infrastructure that powers our GraphQL-based federated query system for seamless data access across platforms including BigTable, BigQuery, and Solr+.

This is a unique opportunity to influence the technical direction of ZoomInfo's core data infrastructure, addressing complex challenges such as data freshness, multi-tenant isolation, and real-time data processing at scale.

Responsibilities:

• Design and build scalable infrastructure for GTM Store and ZDP with sub-second query latency.
• Architect and implement metadata-driven GraphQL APIs for dynamic schema generation and query federation.
• Develop asynchronous secondary indexing systems for scaling capacity and reducing primary data store load.
• Design real-time analytics streaming data pipelines from BigTable to BigQuery.
• Develop data mutation and deletion frameworks supporting GDPR compliance and schema evolution.
• Implement CDC pipelines and calculated field processing for derived data views.
• Build observability and monitoring solutions for real-time issue diagnosis across distributed data systems.
• Create batch and streaming data processing workflows for complex relationships at scale.
• Collaborate with engineering leaders and product managers to define the technical roadmap.
• Mentor engineers and establish best practices for cloud-native data infrastructure development.
• Partner with cross-functional teams to address data platform requirements and challenges.
• Drive solutions for data freshness, query performance, and system reliability challenges.

Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or related field (or equivalent experience).
• 10+ years of software engineering experience building large-scale data platforms.
• Expertise with distributed NoSQL databases and data warehousing systems.
• Strong experience with Java 8+, Scala, Kotlin, GoLang for data systems development.
• Proven experience with GCP or AWS and cloud-native architectures.
• Experience with streaming/real-time data processing technologies.
• Strong system design skills for architecting multi-tenant, distributed systems.
• Hands-on experience with Google Cloud Platform services.
• Knowledge of CDC patterns, event sourcing, and streaming architectures.
• Experience solving data freshness and consistency challenges in distributed systems.
• Background in building observability and monitoring solutions for data platforms.
• Familiarity with metadata management and schema evolution.
• Experience with Kubernetes for deploying data services.
• SQL query optimization and performance tuning expertise.
• Experience building GraphQL APIs with federated or metadata-driven schema generation.
• Strong problem-solving skills and the ability to debug complex distributed systems issues.
• Excellent communication skills for explaining technical decisions to diverse audiences.
• Self-directed with the ability to drive initiatives independently while collaborating with teams.
• Passion for building reliable, observable, and maintainable systems.
• Experience promoting diverse, inclusive work environments.

Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process.

We want our employees and their families to thrive. In addition to comprehensive benefits we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here.

Below is the US base salary for this position. Additional compensation such as Bonus, Commission, Equity and other benefits may also apply.

$163,800-$257,400 USD

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Your work will directly shape what users experience: designing APIs that serve rich content, building services that handle real-time interactions, implementing content-matching systems for rights and safety, and ensuring our platform performs under load. You'll architect systems that are fast, correct, and maintainable.

You'll collaborate closely with Product, ML Research, and Mobile/Web teams to ship features that matter. We use Python, Go, BigQuery, Pub/Sub, and a microservices architecture,but we care more about good judgment than specific tool experience.

Responsibilities

• Design and maintain application-level data models that organize rich content into canonical structures optimized for product features, search, and retrieval.
• Build high-reliability ETLs and streaming pipelines to process usage events, analytics data, behavioral signals, and application logs.
• Develop data services that expose unified content to the application, such as metadata access APIs, indexing workflows, and retrieval-ready representations.
• Implement and refine fingerprinting pipelines used for deduplication, rights attribution, safety checks, and provenance validation.
• Own data consistency between ingestion systems, application surfaces, metadata storage, and downstream reporting environments.
• Define and track key operational metrics, including latency, completeness, accuracy, and event health.
• Collaborate with Product teams to ensure content structures and APIs support evolving features and high-quality user experiences.
• Partner with Analytics and Research teams to deliver clean usage datasets for experimentation, model evaluation, reporting, and internal insights.
• Operate large analytical workloads in BigQuery and build reusable Dataflow/Beam components for structured processing.
• Improve reliability and scale by designing robust schema evolution strategies, idempotent pipelines, and well-instrumented operational flows.

Requirements

• Experience building production backend services and APIs at scale
• Experience building ETL/ELT pipelines, event processing systems, and structured data models for applications or analytics
• Strong background in data modeling, metadata systems, indexing, or building canonical representations for heterogeneous content
• Proficiency in Python, Go, SQL, and scalable data-processing frameworks (Dataflow/Beam, Spark, or similar)
• Familiarity with BigQuery or other analytical data warehouses and strong comfort optimizing large queries and schemas
• Experience with event-driven architectures, Pub/Sub, or Kafka-like systems
• Strong understanding of data quality, schema evolution, lineage, and operational reliability
• Ability to design pipelines that balance cost, latency, correctness, and scale
• Clear communication skills and an ability to collaborate closely with Product, Research, and Analytics stakeholders

Nice to Have

• Experience building application-facing APIs or microservices that expose structured content
• Background in information retrieval, indexing systems, or search infrastructure
• Experience with fingerprinting, perceptual hashing, audio similarity metrics, or content-matching algorithms
• Familiarity with ML workflows and how downstream analytics and usage data feed back into research pipelines
• Understanding of batch + streaming architectures and how to blend them effectively
• Experience with Go, Next.js, or React Native for occasional full-stack contributions

Why Join Us

You will design the core data services and pipelines that power our product experience, analytics, and business operations. You’ll work on high-impact data challenges involving real-time signals, large-scale metadata systems, and cross-platform consistency. You’ll join a small, fast-moving team where you’ll shape the structure, reliability, and intelligence of our downstream data ecosystem.

Benefits

• Highly competitive salary and equity
• Quarterly productivity budget
• Flexible time off
• Fantastic office location in Manhattan
• Productivity package, including ChatGPT Plus, Claude Code, and Copilot
• Top-notch private health, dental, and vision insurance for you and your dependents
• 401(k) plan options with employer matching
• Concierge medical/primary care through One Medical and Rightway
• Mental health support from Spring Health
• Personalized life insurance, travel assistance, and many other perks

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We're creating contract-governed supply chains that let us onboard new assets and providers quickly while maintaining the low-latency, high-availability SLOs our business depends on.

Responsibilities:

• Build streaming data pipelines for blockchain data (onchain transactions, staking rewards, validator info) and market data (prices, trades, order books)
• Design and implement data contracts and validation gates that enforce quality and schema compliance at ingestion points

Complexity and Impact of Work:

• Collaborate on designing the architecture for standardized ingestion patterns that enable rapid onboarding of new blockchains and market data feeds
• Establish redundancy and failover patterns to meet Tier 1 availability and freshness SLOs for critical data products

Organizational Knowledge:

• Collaborate with Protocols, Trading, and Custody teams to understand their data needs and design certified data products with clear SLAs
• Partner with Data Platform team on orchestration, storage patterns (BigLake), and metadata management (Atlan)

Communication and Influence:

• Advocate for contract-governed data supply chains and help establish engineering standards for producer patterns across the org
• Contribute to architectural decisions and help mature the team's practices around observability, testing, and operational excellence

Requirements:

• 5-7+ years building streaming or high-throughput data systems: You have experience designing and operating production data pipelines that handle large volumes with low latency and high reliability
• Solid backend engineering skills: You're proficient in Go or Python and have built services that interact with streaming infrastructure (Kafka, pub/sub, websockets, REST APIs)
• Blockchain data familiarity: You understand blockchain concepts and are comfortable working with on-chain data (transactions, events, staking, validators) across multiple chains with different data models
• Data engineering adjacent skills: You're comfortable with data transformation patterns, schema evolution, and working with cloud data warehouses (BigQuery) and storage systems (GCS, BigLake)
• Operational mindset: You have experience deploying and operating services on cloud platforms (preferably GCP), with strong practices around monitoring, alerting, and incident response

Preferred Qualifications:

• Staking data expertise: You've worked with staking rewards, validator data, or proof-of-stake blockchain infrastructure
• Market data systems: You've built systems that ingest and process market data (prices, trades, order books) from exchanges or data vendors
• Infrastructure as code: You have experience with Terraform, Kubernetes, and modern DevOps practices

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