Senior Data Platform Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Relocation assistance

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work

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Application

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Deadline

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About this role

Senior Data Platform Engineer New York City, New York, USA 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

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