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How do you handle schema evolution in a data pipeline or lakehouse without breaking consumers?

A new column is safe; a rename silently corrupts every dashboard downstream. The signal is knowing which changes are compatible, enforcing data contracts in CI, and running expand-contract migrations for the breaking ones.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

A new column is safe; a rename silently corrupts every dashboard downstream. The signal is knowing which changes are compatible, enforcing data contracts in CI, and running expand-contract migrations for the breaking ones.

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Next in this trackHow do you join two streams (or a stream to a table) in a streaming system?Next in this trackExplain SQL set operations (UNION/INTERSECT/EXCEPT) and NULL handling pitfalls.Next in this trackWhat is data skew in a distributed job (Spark), and how do you fix it?
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