Pinecone

Technology

SeniorDataPlatformEngineer

$176–200k New York, New York, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Senior Data Platform Engineer at Pinecone. Skills: Data platform engineering, AI applications, Data pipelines, ETL/rETL. Build ingestion layer. Design pipelines”

What You'll Achieve.

Ship AI applications faster; Ship AI applications more confidently; Support key business decisions; Support regular reporting to Board

Industry & Context.

Technology
Problems you'll solve

Root cause analysis; Troubleshooting; Data-driven decision making

What They're Looking For.

Must Have

4+ years building data pipelines, SQL comfort, Coding skills, Experience with modern orchestrator, Comfort with Docker, Comfort with Kubernetes, Comfort with cloud infrastructure, Experience integrating systems, Hands-on AI coding tools experience, Ability to design systems end-to-end

Nice to Have

Production DBT experience, Experience with semantic layer, Experience with metrics layer, Comfortable with exploratory analysis, Designing experiments a plus, Basic statistical modeling a plus, Exposure to building AI agents, Exposure to building AI applications

What You'll Do.

Build ingestion layer

Pull from third-party APIs

Pull from internal services

Build transform layer

Maintain core business datasets

Write DBT documentation

Build orchestration platform

Operate Airflow-on-Kubernetes

Improve observability

Establish metrics layer

Maintain metrics layer

Curate metric definitions

Curate metric documentation

Manage infrastructure cost

Manage infrastructure performance

Manage BigQuery costs

Manage Cloud Run costs

Keep platform efficient

Lead company-level analyses

Own company-level analyses

Partner with exec stakeholders

Answer business questions

Build views in BI tools

Support business decisions

Support Board reporting

Enable teams to self-serve

Onboard non-DE stakeholders

Help with best practices

Create reusable models

Create reusable tooling

Set standard for AI-assisted data workflow

Establish AI best practices

Establish AI patterns

How You'll Work.

Team & Collaboration

Partner with finance; Partner with GTM; Partner with product; Partner with exec stakeholders; Onboard analysts; Onboard non-DE stakeholders

Communication Scope

Board-level reporting

Process & Methodology

CI/CD

Full Job Description

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 financ

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