Data pipeline testing checklist

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1. 1.release smoke testsDone when: After each deploy, a run on a fixed sample input produces the expected row count and totals in every target table.Risks: data-corruption, wrong-decisions. Tool class: data validation. Usually run by: developer.
2. 2.data integrity and migration testingDone when: For each run, row counts and control totals reconcile between source extract, staging and target, and a mismatch stops publication.Risks: data-corruption, wrong-decisions, regulatory-penalty. Tool class: data validation. Usually run by: QA engineer.
3. 3.compliance checksDone when: Every regulated report traces each figure back to its source tables, and personal fields are masked or dropped before the shared layer.Risks: regulatory-penalty, data-breach. Tool class: test management. Usually run by: product manager.
4. 4.integration testsDone when: An end-to-end run against staging copies of each source and target loads a file above the largest size seen in production with no rows lost, and when the source stream stops sending mid-run, the run is reported as stalled instead of complete.Risks: data-corruption, dependency-failure. Tool class: data validation. Usually run by: developer.
5. 5.regression suiteDone when: Reconciliation and edge-file cases rerun on every change, and any change in sample output totals blocks the merge.Risks: data-corruption, wrong-decisions. Tool class: test management. Usually run by: QA engineer.
6. 6.resilience and failure testingDone when: With the source stream or warehouse paused mid-run, the job retries, resumes from its last checkpoint and loads each record once.Risks: dependency-failure, data-corruption. Tool class: chaos tool. Usually run by: developer.
7. 7.unit testsDone when: Each transform returns the documented output for empty files, oversized files, null keys, duplicate keys and timezone boundaries.Risks: data-corruption. Tool class: unit framework. Usually run by: developer.
8. 8.security scanningDone when: The scan of buckets, staging schemas and service accounts shows no public access and no personal fields outside approved tables.Risks: data-breach. Tool class: DAST scanner. Usually run by: security specialist.
9. 9.analytics and event tracking testsDone when: Each job emits start, end, rows read and rows written, and a run with no end event or a write count of zero raises an alert.Risks: wrong-decisions. Tool class: data validation. Usually run by: developer.