Data Engineer – Airflow / SQL/Snowflake / Python

We are looking for a hands-on Data Engineer who can independently design, build and operate production-grade data pipelines using Apache Airflow. This is a delivery-facing engineering role: you will own complex, multi-dependency DAGs end to end from ingestion and transformation logic through to scheduling, monitoring, failure recovery and performance tuning. The ideal candidate writes production-quality Python, is genuinely strong in SQL (including analytical functions, complex joins and query optimization), and has debugged enough real pipeline failures to have opinions about idempotency, backfills and retry strategy. You will work closely with data architects, analysts and business stakeholders, and will be expected to raise the engineering standard of the pipelines you touch.

Orchestration & Pipeline Engineering

• Design, develop and maintain complex Airflow DAGs involving multi-stage dependencies, dynamic task generation, branching, sensors, task groups and cross-DAG triggers.

• Build pipelines that are idempotent, restart able and backfill-safe, with correct handling of scheduling intervals, catchup behavior, data intervals and time zones.

• Implement robust error handling and recovery -retries with backoff, SLAs, alerting, callbacks, dead-letter handling and clean partial-failure semantics.