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About this interview
A technical interview on Data Modeling, pitched at the medium level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.
What you'll be assessed on
Explain facts vs dimensions and how to choose the right granularity for a fact table
Describe the star schema vs snowflake schema trade-offs for query performance and maintainability
Define the major SCD types (Type 1, 2, 3) and when to apply each
Identify common dimensional modeling anti-patterns (e.g., fact tables with too many dimensions)
Topics covered
Facts vs DimensionsStar SchemaGranularityStar vs SnowflakeSCDsSurrogate KeysConformed DimensionsDimension TypesAnti-PatternsModeling Philosophies
A few sample questions
Just examples to set expectations - the real interview has many more and adapts to your responses.
“In dimensional modeling, how would you describe the difference between a fact table and a dimension table at a conceptual level?
“Imagine a customer moves from New York to California. Walk me through exactly what happens to the customer dimension table under SCD Type 2.
“In a modern cloud warehouse like BigQuery or Snowflake, does the classic argument for star schemas over snowflake schemas still hold? What changes when you have a columnar engine and large-scale parallel joins?