- Design and build pipelines that move data across systems - supporting data lake ingestion, compliance workloads, and cross-domain data flows
- Own pipeline operations end to end: monitoring, incident resolution, data quality, and documentation that lets any team member respond independently
- Identify technical debt and reliability risks and raise them with clear context and proposed next steps
- Design and maintain schemas across relational, warehouse, and lakehouse layers, working with application engineers and product to get data models right
- Build out the platform’s service layer, infrastructure-as-code, and data quality frameworks - this role spans design and implementation
- Contribute to evaluations of the current platform against emerging architectures and tooling, helping produce trade-off analyses and recommendations
- Track and report on platform health metrics: pipeline uptime, failure rates, data freshness, and cost trends
- Mentor peers and junior engineers through code review, pairing, and technical guidance
- Help uphold engineering standards and collaborate cross-functionally with application engineering, product, and analytics as a reliable technical partner
- Share knowledge through documentation and technical discussions
PythonSQLApache Airflow+5 more