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