Machine Learning Engineer
hardmachine-learning-engineer-data-validation
How do ML engineers validate data and schemas to prevent pipeline breakages?
Answer
Data validation prevents silent failures.
Checks include:
- Schema/type validation
- Range and null constraints
- Cardinality and uniqueness
- Drift against reference distributions
Run checks at ingestion and before training/serving. Fail fast on critical breaks and alert with clear ownership.
Related Topics
Data QualityMLOpsReliability