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Airflow Engineer

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Hybrid

Airflow Engineer

EXL Talent Acquisition Team

Airflow Engineer

Skills

PythonLinuxApache Airflow

2 months ago

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Important information


Location:

Chennai, Tamil Nadu, India

Work mode:

Hybrid

Published on:

11 August 2026

What they need


  • 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 environment-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.

  • 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 environment-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.

  • Bachelor’s degree or equivalent experience in Computer Science, Information Technology, Engineering, or a related discipline.

  • 4+ years of overall engineering experience with hands-on Airflow, Python, and Linux/shell exposure.

  • Strong practical understanding of job scheduling, batch/workflow orchestration, production readiness, and operational support processes.

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