Reviewed by Aditya Kumar · Last reviewed 2026-03-24
**Architectural Logic:** A CTE is a named temporary result set (WITH ... AS) scoped to a single statement. **Why use CTEs:** Readability, modular logic, recursion (hierarchies), and avoiding repeated subquery evaluation in some engines. **Scalability:** CTEs may be inlined or...
This easy-level SQL question appears frequently in data engineering interviews at companies like Fossil Group, Kaseya. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (bigquery, snowflake) will help you answer variations of this question confidently.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example.
Architectural Logic: A CTE is a named temporary result set (WITH ... AS) scoped to a single statement. Why use CTEs: Readability, modular logic, recursion (hierarchies), and avoiding repeated subquery evaluation in some engines. Scalability: CTEs may be inlined or materialized—behavior varies by engine. In BigQuery/Snowflake, CTEs are typically not materialized unless hinted; repeated references can re-execute. Cost: Materialized CTEs (e.g., WITH ... MATERIALIZED) increase memory/disk but avoid recomputation; use when referenced multiple times. Example: WITH monthly_sales AS (SELECT DATE_TRUNC('month', order_date) AS month, SUM(amount) AS total FROM orders GROUP BY 1), growth AS (SELECT month, total, (total - LAG(total) OVER (ORDER BY month)) / NULLIF(LAG(total) OVER (ORDER BY month), 0) 100 AS pct_growth FROM monthly_sales) SELECT FROM growth WHERE pct_growth > 10.
RED FLAG: Claiming 'CTEs always materialize' or ignoring engine-specific behavior. PRO MOVE: 'In Snowflake we use CTE_MATERIALIZATION=ALWAYS for recursive CTEs that feed multiple downstream steps to avoid recomputing complex hierarchies.'
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According to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 2 companies. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.