Analytics Engineer, Finance

OpenAI•San Francisco, CA

1d•Hybrid

About The Position

About the Team The Finance Data team is embedded within the CFO Org and is responsible for building internal data products that scale analytics across business teams and drive efficiencies in our daily operations. This team provides technical guidance on high-impact, scalable projects across Finance, and is the subject-matter expert in financial and transactional data that supports our Finance day-to-day operations. About the Role As an Analytics Engineer, you will be setting the foundation to scale analytics across our business functions and impart best data practices for a rapidly growing organization. We aspire to build the Finance team of the future. In addition, you will work collaboratively with key stakeholders in Finance and other business teams to understand their pain points and take the lead in proposing viable, future-proof solutions to resolve them. You will also autonomously lead your own projects that deliver business impact and help cultivate a mature data culture among Finance teams. We are looking for a seasoned engineer who has a proven track record of owning the entire data stack at high transaction volume companies, managing business critical ETL pipelines consumed by non-technical teams. As a generalist “fixer”, you may be deployed across several different Finance domains (e.g. Tax datamart, ERP migration, Procurement automation). For this role we need someone who excels in dynamic environments, adapts quickly to changing needs, and confidently navigates ambiguous or evolving requirements. If you're energized by solving technical problems without a playbook and comfortable wearing multiple hats, this role is for you! To clarify, you will not be responsible for training ML models and neither would we describe this role as ‘product analytics’. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

Requirements

7+ years of experience as an Analytics Engineer or in a similar role (Data Analyst or Data Engineer) with a proven track record in shipping canonical datasets
Empathy towards non-developer stakeholders and their day-to-day pain points
Strong proficiency in SQL for data transformation, comfort in at least one functional/OOP language such as Python or R
Familiarity with managing distributed data stores (e.g. S3, Trino, Hive, Spark), and experience building multi-step ETL jobs coupled with orchestrating workflows (e.g. Airflow, Dagster)
Experience in writing unit tests to validate data products and version control (e.g. GitHub, Stash)
Expert at creating compelling data visualizations with dashboarding tools (e.g. Tableau, Looker or similar)
Excellent communication skills and ability to present data-driven narratives in both verbal and written form to a non-technical audience
Experience solving ambiguous problem statements in an early stage environment

Nice To Haves

Prior experience leading the development of an internal production tool, serving hundreds of cross-functional customers such as Billing Operations, Deal Desk or Go-to-Market teams
Some frontend experience with React, TypeScript, Retool, Streamlit, or building web apps
Good understanding of Spark and ability to write, debug, and optimize Spark jobs

Responsibilities

Understand the data needs of Finance teams, including Revenue, Tax, Procurement, Compute & Infrastructure Accounting, Strategic Finance, and translate that scope into technical requirements
Facilitate the development of data products and tools to for stakeholders to self-service and enable analytics to scale across the company
Lead dimensional design - define, own, and maintain business facing data marts
Be a cross-functional champion at upholding high data integrity standards and SLAs for the timely delivery of data
Build and maintain insightful and reliable dashboards to track both operational and financial Metrics for the Executive team
Contribute to the future roadmap of the Finance team from a data systems perspective
Grow to be an expert in Finance Data and OpenAI’s data architecture

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