Analyze existing Cybermation job schedules, dependency patterns, runtime parameters, execution frequency, owners, success/failure behavior, and operational support expectations.

Review existing shell scripts and API/cURL invocation logic to determine the appropriate Airflow DAG design, task structure, error handling, and retry configuration.

Design, develop, and maintain Apache Airflow DAGs to orchestrate shell scripts, API calls, and dependent jobs with appropriate scheduling and operational controls.

Configure Airflow schedules, task dependencies, retries, logging, alerting hooks, variables, connections, parameters, and workplace-specific configuration as per client standards.

Perform dry runs, unit testing, schedule validation, API response validation, failure/retry validation, and production-readiness checks for migrated jobs.

Create migration mapping, validation evidence, deployment notes, operational runbooks, and support handover documentation.

- Coordinate with client SMEs, application owners, infrastructure teams, and release teams to support deployment, issue triage, initial run monitoring, and hypercare.

📌 Airflow Engineer (Chennai)
🏢 EXL
📍 Chennai