Senior Data Platform Engineer
Build and scale data pipelines for AI applications
Design, deploy, and scale data pipelines that feed analysts, executives, and the Board. You'll own the ingestion, transformation, orchestration, and metrics layers, ensuring data quality and enabling mission-critical analyses. This role offers direct exposure to finance, GTM, product, and executive staff, with a focus on AI-assisted data workflows.
Why This Role?
Direct exposure to finance, GTM, product, and executive staff
Key Responsibilities
- Design and deploy data pipelines that pull from third-party APIs, internal services, and SaaS tools into BigQuery
- Develop and maintain DBT projects, including staging, intermediate, and marts, and ensure data quality
- Operate and improve the Airflow-on-Kubernetes environment for ingest and DBT workloads
- Curate metric definitions and documentation for both human analysts and agents
- Lead mission-critical company-level analyses and partner with stakeholders to answer business questions
Requirements
- Experience with BigQuery, DBT, and Airflow
- Knowledge of data modeling and data quality
- Experience with cloud infrastructure and cost management
- Ability to lead and own mission-critical analyses
Required Skills
Keywords
View Original Description from Ashby Job Boards
Original description from Ashby Job Boards
ABOUT PINECONE Pinecone is the leading vector database for building accurate and performant AI applications at scale in production. Pinecone’s mission is to make AI knowledgeable. More than 9000 customers across various industries have shipped AI applications faster and more confidently with Pinecone’s developer-friendly technology. Pinecone is based in New York and raised $138M in funding from Andreessen Horowitz, ICONIQ, Menlo Ventures, and Wing Venture Capital. ABOUT THE ROLE Pinecone is looking for a Senior Data Engineer to own and grow the systems that power how we understand our business. You will design and operate the ingest, transform, orchestration, and metrics layers that feed analysts, executives, and the Board, and you will lead the analyses themselves when the question matters enough. This is a high-ownership role on a small team, with direct exposure to finance, GTM, product, and the executive staff. RESPONSIBILITIES - Own and build the ingestion layer. Design, deploy, and scale pipelines that pull from third-party APIs, internal services, and SaaS tools into BigQuery. Add new sources as the business demands. - Own and build the transform layer. Develop and maintain our DBT project, including staging, intermediate, and marts. Maintain core business datasets: users, organizations, indexes, accounts, usage, revenue. Write tests, snapshots, and documentation. Drive data quality and trust. - Own and build the orchestration platform. Operate the Airflow-on-Kubernetes environment that runs our ingest and DBT workloads. Improve reliability, scalability, observability, and CI/CD. - Establish and maintain the business-context and metrics layer. Curate metric definitions and documentation that feed both human analysts and agents. - Manage infrastructure cost and performance. Manage BigQuery, GKE, Cloud Run, and Kafka costs, right-size compute, and make sure the platform stays efficient. - Lead and own mission-critical company-level analyses. Partner with finance, GTM, product, and exec stakeholders to answer business questions, design metrics, run experiments and evaluations, build views in BI tools, and ship dashboards that support key business decisions as well as regular reporting to the Board of Directors. - Enable other teams to self-serve. Onboard analysts and non-DE stakeholders onto the warehouse, help them with best practices, and create reusable models and tooling. - Set the standard for AI-assisted data workflow. Establish best AI practices and patterns that enable a small data team to operate with outsized leverage. QUALIFICATIONS - 4+ years building and operating data pipelines in production. - Strong SQL, with comfort in BigQuery (or Snowflake/Redshift) writing non-trivial analytical queries, optimizing performance, and reasoning about correctness. - Strong coding skills, with comfort writing ETL/rETL, consuming services and integrations against REST/GraphQL APIs, and producing clean code that others can reuse and maintain. - Experience with a modern orchestrator (Airflow, Dagster, Prefect, or similar) running containerized workloads. - Comfort with Docker, Kubernetes, and modern cloud infrastructure best practices. - Experience integrating systems, pulling data between APIs, databases, and warehouses; handling auth, pagination, schema drift, and incremental loads. - Hands-on experience using AI coding tools (Claude Code, Cursor, or similar) as part of your workflow. - Ability to design, build, and own systems end-to-end in a highly autonomous environment. NICE TO HAVE - Production DBT experience: layered models, tests, snapshots, macros, deferred builds. - Experience working with a semantic layer, metrics layer (DBT Semantic Layer, Cube, LookML). - Comfortable with exploratory analysis, designing experiments and A/B tests, basic statistical modeling, and separating signal from noise in messy data. - Exposure to building AI agents or applications. - Infrastructure-as-code (Terraform, Pulumi, or similar). PERKS & BENEFITS - Comprehensive health coverage including medical, dental, vision, and mental health resources - 401(k) Plan - Equity award - Flexible time off - Paid parental leave - Annual Company Event - WFH Equipment Stipend All qualified applicants will receive considerations for employment without regard to race, color, religion, sex, age, disability, marital status, familial status, sexual orientation, pregnancy, gender identity, gender expression, national origin, ancestry, citizenship status, veteran status, and any other legally protected status under federal, state, or local anti-discrimination laws.
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