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Airflow Python Developer/Migration

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Remote

Airflow Python Developer/Migration

Flexton Inc.

Airflow Python Developer/Migration

Skills

SQL QueriesDockerFlaskPythonJavaGrafanaPrometheusLinuxKubernetesFastAPIApache Airflow

18 days ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Remote

Published on:

2 October 2026

What they need


Airflow Developer – UC4/Automic Migration

Experience: 5+ years

Location: Bangalore – Hybrid / Office as per eBay requirements

Project Overview

The role will support the migration of enterprise batch workflows from UC4/Automic to Apache Airflow. The primary focus will be Python/Airflow development, recreating existing UC4 workflows as Airflow DAGs and supporting the migration. The existing migration tooling is Java-based. The role also includes filling Airflow feature gaps and supporting enhancements to the migration tool.

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

  • Strong hands-on Python development experience, with the ability to write clean, testable and reusable code and build reusable components/libraries.
  • Strong 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.
  • Good Linux/Unix and Shell scripting skills.
  • Hands-on experience with one or more Python frameworks/libraries such as FastAPI, Flask, Pydantic, Jinja2 or Celery.

Preferred Skills

  • UC4/Automic workflow/job scheduling experience (highly preferred).
  • Experience migrating UC4 or other enterprise scheduler workloads to Airflow.
  • Git/CI/CD exposure; Docker/Kubernetes knowledge is a plus.
  • Airflow monitoring/observability experience with Prometheus/Grafana or similar tools.
  • Java exposure is an advantage for the existing migration tooling.

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