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

Outline Amazon Redshift's architecture (leader node, compute nodes, columnar storage) and the evolution to RA3 nodes with managed storage. As a data engineer, explain distribution styles, sort keys, and how Redshift handles storage and compute scaling.

MediumTechnical

26 practiced

Estimate monthly cost for a proposed analytics workload: 50 TB stored, 3 TB daily ingest, and an expected 200 TB scanned per month in queries. Choose one provider (Snowflake/BigQuery/Redshift) and list assumptions, cost components, and how you might reduce 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.

MediumTechnical

30 practiced

Explain how Change Data Capture (CDC) can be implemented to feed a cloud warehouse: discuss capture (Debezium, DB logs), transport (Kafka/pubsub), transform (AVRO/CDC envelopes), and apply (MERGE into warehouse). Include how you guarantee exactly-once semantic or idempotency.

MediumTechnical

25 practiced

You are designing governance for a multi-team analytics platform on a cloud data warehouse. Outline components you would include: data catalog, lineage, schema registry, policy enforcement, and how you'd measure governance adoption.

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