2 days ago
Base Salary
$189k - $252k/yr
Responsibilities
- Gather data requirements from User Safety & Risk Operations teams and define datasets and reporting needs.
- Build, maintain, monitor, and troubleshoot production data pipelines and Airflow DAGs, including scheduling, dependencies, and backfills.
- Create reusable data models, reporting cubes, and shared operational reporting metrics.
- Implement data quality and freshness checks and document data lineage, ownership, sources, and transformations.
- Design datasets and reporting with appropriate access and privacy requirements.
- Take projects from initial requirements through production use and maintain systems as team needs evolve.
Requirements
- Strong SQL skills and practical Python experience building and maintaining data pipelines.
- Experience building and debugging scheduled pipelines relied upon by other users.
- Practical understanding of data modeling, joins, deduplication, tests, and monitoring.
- Ability to trace metrics to their inputs and explain appropriate downstream conclusions.
- Experience partnering with non-engineers to translate ambiguous needs into dependable data products.
- Experience with Airflow or similar workflow orchestration tools is preferred.
- Experience transferring prototypes or new workflows into reliable, scaled operations is preferred.
Benefits
- San Francisco-based work model with three days in the office.
- The role may involve exposure to sensitive or concerning content and requires discretion, judgment, and resilience.
About OpenAI
OpenAI builds and deploys large-scale AI models and tools—including ChatGPT, GPT-4–class models, DALL·E, and Whisper—sold via APIs and enterprise subscriptions to developers and businesses. It monetizes through usage-based API pricing and ChatGPT Plus/Team/Enterprise, and also reaches customers via Microsoft’s Azure OpenAI Service. Founded in 2015 and headquartered in San Francisco, it operates as a private partnership.