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.

In this role, you will:

• 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

You might thrive in this role if you have:

• 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

You could be an especially great fit if you have:

• 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

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.

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