Analytics Engineer, Finance

at OpenAI
📍 San Francisco, United States
USD 220,000-270,000 per year
SENIOR
✅ Hybrid
✅ Relocation

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

TypeScript @ 4 Python @ 4 SQL @ 7 Looker @ 4 R @ 4 Spark @ 3 Tableau @ 4 ETL @ 3 Airflow @ 4 GitHub @ 4 Communication @ 4 Dagster @ 4 Data Engineering @ 7 React @ 4 Debugging @ 7 Hive @ 3 Trino @ 3

Details

The Finance Data team (within the CFO org) builds internal data products that scale analytics across business teams and drive efficiencies in daily Finance operations. This role is focused on owning and scaling the data stack for Finance, delivering reliable canonical datasets, and enabling self-service analytics for non-technical stakeholders. This position is based in San Francisco, CA, uses a hybrid work model (3 days in office per week), and offers relocation assistance to new employees.

Responsibilities

  • Understand data needs across Finance domains (Revenue, Tax, Procurement, Compute & Infrastructure Accounting, Strategic Finance) and translate them into technical requirements.
  • Facilitate development of data products and tools to enable stakeholder self-service and scale analytics across the company.
  • Lead dimensional design: define, own, and maintain business-facing data marts.
  • Uphold high data integrity standards and SLAs for timely delivery of data.
  • Build and maintain insightful and reliable dashboards to track operational and financial metrics for the Executive team.
  • Contribute to the Finance data roadmap and data systems architecture.
  • Autonomously lead projects that deliver business impact and cultivate a mature data culture in Finance.

Requirements

  • 7+ years of experience as an Analytics Engineer or in similar roles (Data Analyst, Data Engineer) with a proven track record shipping canonical datasets.
  • Strong proficiency in SQL for data transformation.
  • Comfort with at least one functional/OOP language such as Python or R.
  • Familiarity with managing distributed data stores (e.g. S3, Trino, Hive, Spark) and building multi-step ETL jobs.
  • Experience orchestrating workflows (e.g. Airflow, Dagster).
  • Experience writing unit tests to validate data products and using version control (e.g. GitHub, Stash).
  • Expert at creating compelling data visualizations and dashboards (e.g. Tableau, Looker or similar).
  • Excellent communication skills and ability to present data-driven narratives to non-technical audiences.
  • Experience solving ambiguous problem statements in early-stage or dynamic environments.
  • This role is not responsible for training ML models and is not described as product analytics.

Nice to have

  • Prior experience leading development of internal production tools serving hundreds of cross-functional customers (Billing Ops, Deal Desk, GTM teams).
  • Frontend experience with React, TypeScript, Retool, or Streamlit.
  • Deep experience with Spark including writing, debugging, and optimizing Spark jobs.

Compensation & Benefits

  • Base salary range: $220,000 - $270,000 (offers equity). Base pay may vary depending on location, knowledge, skills, and experience.
  • Relocation support for eligible employees.
  • Medical, dental, and vision insurance with employer contributions to HSAs; pre-tax accounts (FSA, Dependent Care, commuter); 401(k) with employer match.
  • Paid parental leave, paid medical and caregiver leave, flexible PTO, paid company holidays, and paid sick/safe time as required by law.
  • Mental health and wellness support, employer-paid basic life and disability coverage, annual learning stipend, daily meals in offices / meal credits, and other fringe benefits.
  • Background checks and reasonable accommodations information provided per company policy.