Design tables for event-driven metrics
MetaData Engineer · Technical Screen
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This question evaluates relational data modeling and data engineering competencies for high-volume event analytics, including schema design, partitioning and clustering strategies, duplicate and late-arriving event handling, and normalization versus denormalization trade-offs.
Design a relational schema to store user events for a consumer app so that the metrics above can be computed efficiently. Provide table definitions with columns and data types, primary/foreign keys, partitioning and indexing strategy, and sample rows. Explain normalization versus denormalization choices, how to handle late-arriving or duplicated events, and how to support backfills and incremental fact tables.
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