Prepare for your Snowflake data engineering interview
Cloud data warehouse and Snowpark engineering cases calibrated to Snowflake’s cloud-native, data-sharing-first platform culture.
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The Interview
What Snowflake is looking for
Warehouse Design Interview
Cloud Data Warehouse Architecture
01Virtual Warehouse Sizing & Auto-Scaling
02Clustering Keys & Micro-Partition Pruning
03Materialized View & Query Optimization
04Data Sharing & Marketplace Design
Pipeline Case Interview
Data Pipeline & Ingestion
01ELT Pipeline Design with Snowpipe
02Schema Drift Detection & Handling
03Incremental vs Full Refresh Strategy
04Cost Attribution & Query Profiling
Behavioral Interview
Behavioral Interview
01Cloud Data Architecture Trade-offs
02Cross-Team Data Governance
03Query Performance Ownership
04Data Cost Reduction Initiatives
Snowflake-native query optimization and clustering//Snowpipe and ELT pipeline design cases//Cloud data warehouse cost-performance trade-offs
Practice Library
