Azure Lead Data Engineer designing and developing ETL/ELT pipelines with Azure Data Factory and Snowflake. Collaborating with cross - functional teams in a cloud - native environment.
About the role
- Data Engineer building data pipelines for AI Safety company. Handling petabytes of logs and creating a clean, reliable data environment.
Responsibilities
- Build and maintain a clean, stable data environment so all team members can access petabytes of traces, logs, and model outputs in the formats they need – without delays or manual extraction.
- Develop and run internal data APIs, SDKs, and tools that help engineering, product, and research teams discover, query, and use data without touching infrastructure.
- Monitor and improve data performance – from table layouts to query plans – so analytics and research workloads stay smooth as volumes grow.
- Manage data access and governance, defining and enforcing permissions, access rules, and security policies.
Requirements
- You’ve built or scaled a modern data stack – Snowflake, ClickHouse, event streaming – in a startup or similarly fast environment.
- You’re strong in SQL and Python and comfortable working with large, messy datasets.
- You communicate clearly and can work directly with engineers and researchers. Fluent English.
- A big plus: experience with Metabase, Tableau, or similar tools for internal dashboards.
Benefits
- 20 days of paid vacation
- Work from Paris (hybrid) + relocation package
- Best medical insurance in France
- All the hardware, tools, and services you need
- Covered subscriptions for AI agents and IDEs
- Team off-sites twice a year: we’ve recently been to the Alps and to Saint-Tropez
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