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Mountain View, California, United States
Onsite
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.
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.
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.
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.
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.
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