**Architectural Logic**: Native = Snowflake-managed storage; External = metadata in Snowflake, data elsewhere. **Native**: Full features (clustering, time travel); data in Snowflake storage. **External**: Data in S3/Azure/GCS; query via Snowflake compute; partition inference....
This hard-level SQL question appears frequently in data engineering interviews at companies like Ford. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (optimization, partition, snowflake) will help you answer variations of this question confidently.
This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.
Architectural Logic: Native = Snowflake-managed storage; External = metadata in Snowflake, data elsewhere. Native: Full features (clustering, time travel); data in Snowflake storage. External: Data in S3/Azure/GCS; query via Snowflake compute; partition inference. Use Native: Curated, frequently queried data. Use External: Raw data; cost optimization; data stays in lake. Scalability: External avoids data movement; native has better query performance. Cost: External storage cheaper (object store); native has Snowflake markup. Best Practice: External for raw/landing; stage and load into native for production; external for infrequent access to large datasets.
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Analyze My Answer — FreeAccording to DataEngPrep.tech, this is one of the most frequently asked SQL 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.