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Handle midstream schema changes gracefully.

System Design/Architectureeasy0.2 min readPremium

**Strategy**: (1) Schema evolution—additive changes; new columns, defaults for old; (2) Schema Registry—versioned, backward/forward compatible; (3) Multiple readers—support versions during transition; (4) Dead-letter for incompatible. **Parquet/Delta**: mergeSchema=True. Avro:...

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Frequency
Low
Asked at 1 company
Category
179
questions in System Design/Architecture
Difficulty Split
15E|6M|158H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Google
Interview Pro Tip

Red Flag: 'We'd restart the pipeline.' Pro-Move: 'Additive-only policy; new columns get default null; backfill job for historical.'

Why This Question Matters

This easy-level System Design/Architecture question appears frequently in data engineering interviews at companies like Google. While less common, it tests deeper understanding that distinguishes strong candidates.

How to Approach This

Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.

Expert Answer
46 words

Strategy: (1) Schema evolution—additive changes; new columns, defaults for old; (2) Schema Registry—versioned, backward/forward compatible; (3) Multiple readers—support versions during transition; (4) Dead-letter for incompatible.

Parquet/Delta: mergeSchema=True. Avro: Schema Registry. Design for evolution; document breaking vs additive; compatibility tests in CI. Google: extensive versioning, canary deployments.

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According to DataEngPrep.tech, this is one of the most frequently asked System Design/Architecture interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.

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