Tasks where the candidate faced failure and lessons learned.

A memorable failure involved a data pipeline that silently dropped records during a schema migration. Situation: We deployed a change that altered column types; null handling differed between dev and prod. The pipeline completed "successfully" but 12% of records were excluded. Approach: We implemented row-count validation at each stage, added dbt tests for uniqueness and completeness, and created alerting on variance from expected volumes. We also introduced a staging-to-production diff before merge. Result: We recovered the missing data via backfill, and the new safeguards caught two similar issues within months. The lesson: never trust pipeline success status alone—validate data correctness with assertions and monitoring.