Reviewed by Aditya Kumar · Last reviewed 2026-03-24
BigQuery benefits: (1) Serverless—no infrastructure management; scale automatically. (2) Pay-per-query—cost based on bytes scanned; separate storage pricing. (3) Fast—columnar storage, distributed execution, Petabyte-scale in seconds. (4) ANSI SQL with extensions—familiar...
This hard-level SQL question appears frequently in data engineering interviews at companies like EY. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (bigquery, partition, sql) will help you answer variations of this question confidently.
This is a senior-level question that tests architectural thinking. Lead with the high-level design, then drill into specifics. Discuss trade-offs explicitly - there is rarely one correct answer. Show awareness of scale, fault tolerance, and operational complexity.
BigQuery benefits: (1) Serverless—no infrastructure management; scale automatically. (2) Pay-per-query—cost based on bytes scanned; separate storage pricing. (3) Fast—columnar storage, distributed execution, Petabyte-scale in seconds. (4) ANSI SQL with extensions—familiar syntax. (5) Integration—native with GCP services, BI tools. (6) ML built-in—BQML for models. (7) Geospatial and JSON support. Best practice: Use partitioning and clustering to reduce scanned bytes; leverage BI Engine for dashboards; avoid repeated full scans with materialized views. Why it matters: Design choices compound at scale—wrong approach can cause 100× overhead. Scalability trade-offs: Profile before optimizing; validate on sample then full. Cost implications: Suboptimal choices multiply at billion-row scale.
Red Flag: Generic textbook answers. Pro-Move: 'At scale we measured X, implemented Y, achieved Z%—validated and iterated.'
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According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.