OpenAI Logo

OpenAI

Data Engineer, Monetization Data Platform

Posted 28 Days Ago
In-Office
2 Locations
Entry level
In-Office
2 Locations
Entry level
Build and operate scalable streaming and batch data pipelines for monetization, financial, and operational data. Develop canonical data models, reusable data products, data quality controls, observability, lineage, reconciliation, and auditability. Partner with Product Engineering, Finance, Accounting, Analytics, and GTM teams to define data contracts and deliver reliable platform capabilities. Lead technical designs, complex cross-functional projects, incident response, and engineering improvements.
The summary above was generated by AI
About the team

The Monetization Data Platform team builds the trusted data and platform foundations that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences.

We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business.

About the role

We are looking for a Data Engineer to improve and build the next generation of our monetization data platform. You will own high-impact systems end to end, from product instrumentation, source ingestion, and canonical modeling through quality controls, observability, and delivery to downstream consumers.

This is a hands-on role for an engineer who enjoys solving ambiguous product and data problems, designing durable architectures, and partnering closely with Product Engineering, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into trusted, scalable data products and platform capabilities.

In this role, you will
  • Design, build, and operate large streaming and batch data pipelines that process product, financial, and operational data from a variety of internal and external systems.

  • Develop canonical data models and reusable data products for domains such as product usage, pricing, billing, ads, payments, revenue, and the general ledger.

  • Establish strong guarantees for data accuracy, completeness, freshness, lineage, reconciliation, and auditability.

  • Build frameworks and platform capabilities that improve developer productivity and make it easier for teams to launch, measure, and iterate on monetization products using trusted data.

  • Partner with Product Engineering, Finance, Accounting, Analytics, and GTM teams to define data contracts, instrument new monetization features, and translate product and business requirements into robust technical solutions.

  • Lead the technical design and delivery of complex, cross-functional projects, using clear system designs and RFCs to align partners before implementation and making sound tradeoffs among speed, scalability, reliability, and maintainability.

  • Improve the observability and operational excellence of critical data workflows, including monitoring, incident response, root-cause analysis, and long-term remediation.

  • Command strong sense of engineering excellence, contribute to a design-before-implementation approach with clear documentation, and knowledge sharing across teams to elevate the broader engineering organization.

You might thrive in this role if you
  • Have deep experience building and operating production data platforms, distributed data systems, or high-scale data pipelines.

  • Are highly proficient in large data pipeline architecture and at least one general-purpose programming language such as Python, Java, or Scala.

  • Have strong fundamentals in data modeling, data architecture, distributed systems, and software engineering.

  • Have designed systems with rigorous data quality, observability, lineage, governance, privacy, or access-control requirements.

  • Can collaborate with cross-functional partners to identify needs, navigate ambiguity, and drive progress from problem definition through delivery.

  • Bring a product-oriented mindset and communicate clearly with technical and non-technical partners, translating customer and business problems into precise data contracts and scalable system designs.

  • Care deeply about correctness and operational reliability while maintaining a practical bias toward delivering value.

  • Bring a strong sense of engineering excellence, using clear thinking, sound judgment, and a design-before-implementation approach to create maintainable systems.

Nice to have
  • Experience with monetization, pricing, product usage, billing, ads, payments, revenue, or financial data.

  • Familiarity with financial controls, reconciliation, close processes, or audit requirements.

  • Experience with modern lakehouse or data warehouse technologies, workflow orchestration, streaming systems, and data transformation frameworks.

  • Experience building self-service data platforms, shared frameworks, or developer tooling used by other data and engineering teams.

  • Monetization or finance domain experience is helpful but not required. We value strong data engineering judgment, systems thinking, and the ability to learn a complex domain quickly.

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.

To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. 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.

OpenAI Global Applicant Privacy Policy

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.

HQ

OpenAI San Francisco, California, USA Office

San Francisco, CA, United States

Similar Jobs

22 Minutes Ago
Remote or Hybrid
USA
112K-229K Annually
Senior level
112K-229K Annually
Senior level
Machine Learning • Payments • Security • Software • Financial Services
Lead and scale enterprise WIAM governance: define policy and control standards, centralize governance, drive risk-to-control traceability, prioritize remediation, monitor KPIs and audit readiness, advise senior stakeholders, and mentor staff to strengthen control effectiveness and regulatory compliance.
Top Skills: Access ControlData Loss PreventionIdentity And Access Management (Iam)Network SecuritySecurity Technologies
4 Hours Ago
Hybrid
23-31 Hourly
Entry level
23-31 Hourly
Entry level
Fintech • Financial Services
Provides banking support across multiple branches, including account openings, service requests, credit applications, cash handling, teller activities, customer outreach, and referrals to financial products and specialists. Builds customer relationships, identifies needs, promotes solutions, adopts digital banking tools, follows risk and compliance controls, and collaborates with branch teams. Requires travel throughout the assigned geography, Saturday availability, SAFE registration, and compliance with loan-originator requirements.
Top Skills: Cash Handling SystemsDigital Banking Tools
4 Hours Ago
Hybrid
38K-67K Hourly
Senior level
38K-67K Hourly
Senior level
Fintech • Financial Services
Lead a Wells Fargo branch team, driving customer acquisition, relationship growth, deposits, lending, credit card, and investment sales. Hire, coach, and develop employees; improve productivity through observation, feedback, and performance management. Partner with wealth, business banking, and home lending teams to meet customer needs. Promote digital banking solutions while balancing growth, operational risk, compliance, loss prevention, and customer protection. Complete the Branch Manager Readiness Program before placement, with possible travel up to 50% during the first six months.

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account