Technical Operations Analyst, User Safety & Risk Operations

About the Team

At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We translate real-world user and operational signals into timely decisions, practical interventions, and improvements to our products and systems.

This role sits on the Risk Incubation & Systems (RIS) team, which investigates emerging risks, builds data and automation capabilities, and develops workflows that can scale into durable operational homes.

About the Role

You'll build and maintain the data pipelines and shared datasets that teams across USRO use for analysis, measurement, and automation. Working with operational teams and engineers, you'll turn data from different systems into reliable sources that colleagues can use in their work.

You'll take projects from initial requirements through to production use, with responsibility for testing and documentation. As teams' needs change, you'll help maintain and extend the systems you build.

Location / work model: San Francisco based with three days in the office.

Please note: This role may involve exposure to sensitive or concerning content. Strong discretion, good judgment, and resilience are essential.

In This Role, You Will

• Work with USRO teams to understand their data needs and define requirements for datasets and reporting.
• Build, maintain, and monitor production data pipelines and Airflow DAGs, including scheduling, dependencies, backfills, and troubleshooting failures.
• Build and maintain reusable data models, reporting cubes, and shared operational reporting metrics, so teams can use consistent definitions across dashboards and analyses.
• Set up data quality and freshness checks, document lineage and ownership, and make the work supportable after handoff.
• Document data sources and transformations so colleagues can trace results back to the underlying records.
• Apply access and privacy requirements when designing datasets and reporting.

You Might Thrive in This Role If You

• Have strong SQL skills and practical experience using Python to build and maintain data pipelines.
• Have built and debugged scheduled pipelines that other people depend on.
• Practical understanding of data modeling, joins, deduplication, tests, and monitoring.
• Ability to trace a surprising metric back to its inputs and explain what downstream users can and can't conclude.
• Experience partnering with non-engineers to turn ambiguous needs into dependable data products.

Nice to Have

• Experience with Airflow or similar workflow orchestration tools.
• Experience transferring prototypes or new workflows into reliable, scaled operations.