Data Engineer, Safeguards

As a Data Engineer on the Safeguards team, you will build the data foundations that keep our AI systems safe. You'll design and build pipelines, warehousing solutions, and analytical tooling to support safety and trust efforts at scale, working with engineers, data scientists, and policy teams.

• Design, build, and maintain scalable data pipelines for safety monitoring, abuse detection, and enforcement.
• Develop and optimize data models and warehousing solutions for large-scale usage and safety data.
• Build dashboards and reporting infrastructure for visibility into model behavior and misuse patterns.
• Integrate data from multiple sources into a unified analytical layer.
• Implement data quality frameworks, monitoring, and alerting.
• Develop self-service data tooling and contribute to data governance.

• Proficiency in SQL and Python, with hands-on experience building and maintaining ETL/ELT pipelines.
• Experience with cloud data platforms such as BigQuery, Redshift, Snowflake, or similar.
• Experience with modern data stack tools such as dbt, Airflow, Spark, or similar.
• Experience building dashboards and data visualizations using tools such as Looker, Tableau, or Metabase.
• Ability to communicate clearly and translate complex data concepts.

• 8+ years of experience in data engineering or analytics engineering.
• Background in trust and safety, integrity, fraud, or abuse detection data systems.
• Experience with large-scale event streaming systems such as Kafka, Pub/Sub, or Kinesis.
• Experience building data infrastructure for ML model monitoring or evaluation.
• Familiarity with data privacy and compliance frameworks such as GDPR, CCPA.
• Background in statistical analysis.

Annual salary: $320,000—$405,000 USD.

San Francisco, CA or New York City, NY. Currently, we expect all staff to be in one of our offices at least 25% of the time.

We do sponsor visas.