Job description

ABOUT THE TEAM The Applied organization brings OpenAI’s most advanced technology to the world through products like ChatGPT and the APIs that power a growing ecosystem of developer and enterprise applications. Data Engineering builds and operates the trustworthy, secure, and reliable data systems that power decisions across OpenAI. ABOUT THE ROLE We’re looking for a Data Engineering Manager to lead the Growth & Revenue data engineering team. This leader will own the data strategy and execution for the data subject areas spanning growth accounting across all product surfaces, product partnerships, checkout, billing, payments, revenue, and monetization, helping OpenAI understand how people adopt, engage with, and pay for our products. You will partner closely with several Data Science, Business, and Engineering partners to connect product behavior to trustworthy subscriber, payment, and revenue measurement. IN THIS ROLE, YOU WILL: - Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas. - Define the data strategy for all the data subject areas you own. - Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue. - Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions. - Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics. - Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems. - Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response. - Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have deep experience leading and scaling data engineering teams in a fast-moving product or technology environment. - Bring strong technical judgment across modern data systems, including SQL, Python or Scala, Spark, orchestration, dimensional and event modeling, and lakehouse or warehouse architectures. - Have built trusted growth, lifecycle, attribution, subscription, billing, payments, revenue, or monetization data products at meaningful scale. - Can turn ambiguous business questions into durable data contracts, metric definitions, and technical roadmaps. - Build unusually strong partnerships with Data Science, Product, Finance, Financial Engineering, GTM, and Engineering. - Care deeply about data quality, privacy, security, and the operational health of systems used for consequential decisions. - Are an excellent people leader: you hire well, develop talent, give clear feedback, and create an environment where diverse perspectives do their best work. WHAT SUCCESS LOOKS LIKE - In the first 90 days, you have earned trust with the team and partners, clarified ownership boundaries, assessed the current data portfolio, and aligned on a prioritized roadmap. - Within a year, Growth & Revenue stakeholders rely on a smaller set of trustworthy, well-owned datasets and metrics for lifecycle, attribution, subscriber, billing, payment, monetization, and revenue decisions. - The team operates with clear goals, healthy execution rhythms, strong reliability standards, and a hiring and development plan that matches the domain’s ambition. This role is based in our San Francisco headquarters. We offer relocation assistance for new employees. 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 cdn.openai.com. 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. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form form.asana.com. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link form.asana.com. OpenAI Global Applicant Privacy Policy cdn.openai.com At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Requirements

Must-haves

Build, manage, and grow a high-performing, inclusive team across the Growth & Revenue data subject areas.
Define the data strategy for all the data subject areas you own.
Deliver durable, well-modeled data products that connect product behavior, subscription state, checkout events, payment outcomes, and revenue.
Establish trusted metric definitions and data quality standards so product, growth, finance, and executive leaders can make fast, consistent decisions.
Partner with Data Science and Product teams to support experimentation, causal measurement, funnel analysis, and scalable self-serve analytics.
Partner with Finance and Financial Engineering to ensure analytical revenue views reconcile to financial truth and production billing systems.
Raise operational excellence for critical pipelines, including reliability, observability, privacy, governance, and incident response.
Set a clear roadmap, make principled tradeoffs, and communicate progress and risk across technical and business stakeholders.
YOU MIGHT THRIVE IN THIS ROLE IF YOU:
Have deep experience leading and scaling data engineering teams in a fast-moving product or technology environment.
Bring strong technical judgment across modern data systems, including SQL, Python or Scala, Spark, orchestration, dimensional and event modeling, and lakehouse or warehouse architectures.
Have built trusted growth, lifecycle, attribution, subscription, billing, payments, revenue, or monetization data products at meaningful scale.
Can turn ambiguous business questions into durable data contracts, metric definitions, and technical roadmaps.
Build unusually strong partnerships with Data Science, Product, Finance, Financial Engineering, GTM, and Engineering.
Care deeply about data quality, privacy, security, and the operational health of systems used for consequential decisions.
Are an excellent people leader: you hire well, develop talent, give clear feedback, and create an environment where diverse perspectives do their best work.
In the first 90 days, you have earned trust with the team and partners, clarified ownership boundaries, assessed the current data portfolio, and aligned on a prioritized roadmap.
Within a year, Growth & Revenue stakeholders rely on a smaller set of trustworthy, well-owned datasets and metrics for lifecycle, attribution, subscriber, billing, payment, monetization, and revenue decisions.
The team operates with clear goals, healthy execution rhythms, strong reliability standards, and a hiring and development plan that matches the domain’s ambition.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

sqlpythonai

Platform: ashby
Effort: quick