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Cloud Data Warehouse Architecture Questions

Understand modern cloud data platforms: Snowflake, BigQuery, Redshift, Azure Synapse. Know their architecture, scalability models, performance characteristics, and cost optimization strategies. Discuss separation of compute and storage, time travel, and zero-copy cloning.

EasyTechnical
27 practiced
Describe zero-copy cloning in Snowflake. As a data engineer, explain how it works (metadata pointers vs physical copies), common uses (dev/test, branching), and potential pitfalls related to long-lived clones and clone churn on storage costs.
HardTechnical
48 practiced
Explain the internal storage/execution differences between Snowflake micro-partitions, Parquet/ORC columnar files, and Dremel's execution model (BigQuery). As a data engineer, say how these affect predicate pruning, columnar reads, and per-query bytes scanned.
EasyTechnical
22 practiced
Write a SQL MERGE statement in BigQuery (Standard SQL) to perform an upsert from a staging table staging.events into analytics.events, deduplicating on event_id and choosing latest event_ts if duplicates exist. Provide assumptions about partitions and constraints.
HardSystem Design
22 practiced
Design a unified lakehouse architecture that integrates object storage (S3/GCS) with a cloud warehouse (e.g., Snowflake external tables or BigQuery federated sources). Address metadata management, format selection, performance for interactive queries at 100 TB, and governance.
HardTechnical
24 practiced
Design an analytics schema for high-cardinality user event data to support fast sessionization queries and GDPR right-to-be-forgotten deletions. Discuss how you would structure facts and dimensions, indexing/clustering, and approaches to delete or mask user data efficiently.

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