Key Responsibilities :
Develop, enhance and troubleshoot Apache Airflow DAGs using Python.
Build custom operators, sensors, scheduling and dependency logic.
Analyze and migrate UC4/Automic workflows to Airflow.
Support batch scheduling, remote job execution and migration validation.
Validate migrated workflows for dependencies, timing and output parity.
Troubleshoot DAG/workflow issues and support Airflow monitoring.
Contribute to migration tooling enhancements where required.
Required Skills :
Robust hands-on Python development experience, with the ability to write clean, testable and reusable code and build reusable components/libraries.
Solid hands-on Apache Airflow development – DAGs, custom operators, hooks/sensors, scheduling, dependencies and debugging.
Experience with workflow/batch orchestration or migration.
Working knowledge of SQL and ETL/data pipeline fundamentals.
Positive Linux/Unix and Shell scripting skills.
Hands-on experience with one or more Python frameworks/libraries such as FastAPI, Flask, Pydantic, Jinja2 or Celery.