Data pipelines fail in quiet ways. A job runs green while silently dropping rows. Reliability comes from designing for failure, not hoping to avoid it.
Make reruns safe
Design tasks to be idempotent so re-running a failed job produces the same result instead of duplicating data. This single property removes a whole class of 3 a.m. incidents.
Watch the data, not just the job
- Track row counts and freshness, not only success and failure.
- Validate schemas at ingestion so bad data fails loudly and early.
- Alert on anomalies in volume, not just on crashes.
A pipeline you can trust is one that tells you when something is wrong — before your stakeholders do.