I will build apache airflow dags with backfills retries and alerting
Data Engineer Python SQL Spark AWS GCP Airflow dbt
Informazioni su questo servizio
I build production-ready Airflow DAGs that are safe to operate: rerun-safe tasks, backfills, retries, and alerting.
What you get:
- Clean DAG structure and task boundaries
- Retry and timeout strategy
- Backfill and reprocess approach (where applicable)
- Alerting guidance (Slack/email/webhook)
- Documentation and a handover call
Scope notes:
- Fixed scope per package (sources and DAG count). Additional DAGs or sources are add-ons.
- I can work with repo access or deliver a zipped project.
- Credentials should be least-privilege.
Choose a package, share your source and destination, and I will implement a DAG your team can run in production.
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FAQ
What do you consider “1 task” or “1 DAG”?
A DAG is one workflow file. Tasks are operator steps inside the DAG.
What counts as a revision?
Changes within the agreed DAGs and integrations. New DAGs or new systems are add-ons.
Can you work with MWAA or Composer?
Yes. Premium includes hardening guidance. Full infra build can be added.
Do you handle backfills?
Standard and Premium include backfill strategy. Backfill execution can be scoped if needed.
What alert channels do you support?
Slack, email, webhook, and typical Airflow alerting patterns.
Can you integrate APIs and databases?
Yes. Provide sample payloads or schemas.

