How do you manage schema evolution in an analytics pipeline?
This tests your grasp of data as a contract. A great answer covers schema registries, backward compatibility, and a phased rollout from producer to warehouse. A red flag is only mentioning an `ALTER TABLE` command, ignoring the entire data pipeline.
This tests your understanding of data as a contract and operational maturity. A strong answer outlines a zero-downtime change using a schema registry to enforce backward compatibility, details a phased rollout (consumers first, then producers), updates the warehouse with a metadata-only change, and discusses the business trade-offs of backfilling historical data. A major red flag is suggesting a solution that only involves the database, ignoring the upstream event pipeline and risking data loss.
Read the original → branchboston.com
- #data engineering
- #schema evolution
- #system design
- #analytics
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