Data Engineering Manager

Required

• 5+ years in data engineering, including 1+ years as a people manager with direct reports. First-time managers with strong early results are welcome.
• Still writing production code today, with deep experience in dbt and an orchestrator such as Airflow on a cloud warehouse such as Snowflake.
• Experience designing data systems end to end, not just building within an existing design, and making sound architectural tradeoffs.
• Strong pipeline best practices: testing, CI/CD for data, modular modeling, code review and documentation.
• Hands-on experience with data monitoring and observability: alerting, freshness and quality checks, lineage and incident response.
• Experience implementing data access, security, and privacy controls, such as role-based access, PII masking, and retention.
• Experience preparing data for AI use, such as semantic layers or well-documented datasets that agents and LLM tools can query safely.
• Daily, practical use of AI tools in your own engineering work, and enthusiasm for helping a team adopt them.
• An enablement mindset: you measure success by how much faster other teams move, not by how much you control.
• Excellent communication, written and spoken, with technical and non-technical audiences.