Contact person: Business Client

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Location: Delhi, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I have an Airflow pipeline written in Python whose sole purpose is data transformation, and it’s not behaving as expected. I need someone to jump in right away, review the existing DAG, correct the logic or write missing pieces, and then validate that every transformation scenario runs cleanly end-to-end.

Scope of work
• Inspect the current DAG structure, task dependencies, schedules, and Python operators.
• Patch or rewrite any sections that break the transformation flow, including hooks, sensors, and custom Python functions.
• Create or update unit tests and an Airflow test run so each transformation scenario (success path, retries, failure alerts) is covered.
• Hand over the updated DAG, a short README explaining configuration variables, and evidence of a green test run in my environment.

Acceptance criteria
• DAG is visible in the Airflow UI without import errors.
• All tasks succeed when triggered manually and on schedule.
• Retry logic, alerting, and failure handling behave exactly as coded.
• Code follows PEP8 and Airflow best practices.

Timeline is ASAP, so I’ll prioritise freelancers who can demonstrate solid Airflow experience and can start immediately. When you respond, briefly outline similar transformation pipelines you’ve fixed or built and your estimated turnaround." (client-provided description)