Notion·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

SQL-heavy technical screen for a data engineering role at Notion. One question, pretty focused, centered on aggregation logic and the edge cases around it.

Questions Asked (1)

Given a transactional or event table, write a SQL query that groups rows by one or more columns and returns aggregate metrics per group. Walk through your reasoning on GROUP BY rules, when to use HAVING versus WHERE, and how you handle NULLs in grouped columns.

Data ModelingTechnical Trade-offs

Author's notes

I got the basic query down fine but stumbled a bit when they pushed on NULLs.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the table schema and the exact metrics needed, then write a SQL query that uses GROUP BY on the specified columns and aggregate functions like COUNT, SUM, or AVG. Explain the logical order of SQL execution to justify using WHERE for pre-aggregation filtering and HAVING for post-aggregation filtering, and address NULL handling in grouping columns by using COALESCE or IS NULL checks.

Pro tip: Mention that NULLs are treated as a single group in GROUP BY, which can lead to unexpected results; proactively suggest using COALESCE or filtering them out if they are not meaningful. Also, note that some databases allow grouping by column aliases or positions, but it's best to avoid that for portability and readability.

1. Clarify requirements and schema

Ask about the table structure, the columns to group by, the desired aggregate metrics, and any filtering conditions. Confirm whether NULLs should be included or excluded.

2. Write the base query with GROUP BY

Select the grouping columns and aggregate functions, then add the GROUP BY clause with those columns. Ensure all non-aggregated columns in the SELECT are in the GROUP BY.

3. Apply filtering with WHERE and HAVING

Use WHERE to filter rows before grouping (e.g., date ranges, status). Use HAVING to filter groups after aggregation (e.g., count > 10). Explain the logical order: FROM → WHERE → GROUP BY → HAVING → SELECT → ORDER BY.

4. Handle NULLs in grouping columns

Decide whether to include NULLs as a group or exclude them. Use COALESCE to replace NULLs with a default value, or add IS NOT NULL in WHERE to exclude them. Mention that NULLs are grouped together by SQL.

5. Review and optimize

Check for correctness, consider indexing on grouping columns, and discuss performance implications of large datasets. Optionally, mention window functions as an alternative for running totals or rankings.

Key Points to Mention

GROUP BY rules: all non-aggregated columns in SELECT must appear in GROUP BY; aggregate functions ignore NULLs except COUNT(*).
WHERE vs HAVING: WHERE filters rows before grouping, HAVING filters groups after aggregation; HAVING can reference aggregates.
NULL handling: NULLs form their own group in GROUP BY; use COALESCE or IS NULL to manage them explicitly.
Logical query processing order: FROM, WHERE, GROUP BY, HAVING, SELECT, ORDER BY, LIMIT.
Performance considerations: indexing grouping columns, avoiding unnecessary columns in GROUP BY, and using appropriate aggregate functions.
Portability: avoid grouping by column aliases or positions; use explicit column names for clarity and cross-database compatibility.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.