SQL Interview Questions

Q: What are the most common SQL interview questions?

The most common SQL interview questions test JOINs (INNER, LEFT, RIGHT), window functions (ROW_NUMBER, RANK, LAG/LEAD), aggregations (GROUP BY, HAVING), CTEs and subqueries, and CASE WHEN statements. Companies like Meta, Google, and Amazon frequently ask about deduplication, top-N per group, and funnel analysis patterns.

Q: How should I prepare for SQL interviews at FAANG companies?

Focus on mastering window functions, complex JOINs, and CTEs. Practice 50-100 Medium difficulty problems, timing yourself to solve each in 15-20 minutes. Learn company-specific patterns: Meta emphasizes metrics and user behavior analysis, Amazon tests data aggregation and reporting, Google focuses on analytical thinking with SQL. Practice explaining your thought process out loud.

Q: What difficulty level should I practice for SQL interviews?

Start with Easy problems to build confidence and master fundamentals. Focus 70% of your time on Medium difficulty, which represents most real interview questions. Practice Hard problems if interviewing for senior roles (L5+) or companies known for difficult technical screens like Meta or Google. Aim to solve Medium problems in 15-20 minutes.

Q: Are SQL interviews the same for Data Scientists and Data Analysts?

Both roles are tested on SQL fundamentals, but with different emphasis. Data Scientists face more complex analytical queries involving statistical calculations, user cohorts, and A/B testing analysis. Data Analysts are tested more on reporting queries, business metrics, and dashboard-ready outputs. Data Scientists typically get 1-2 harder SQL problems, while Analysts may get 2-3 medium problems in the same time.

Q: Can I use online resources during SQL interviews?

Most companies (Meta, Google, Amazon, Netflix) do NOT allow internet access during SQL interviews. You're expected to write queries in shared editors like CoderPad without running them. Exceptions include Robinhood and DoorDash which allow searching, but relying on search wastes valuable time. Practice writing syntactically correct SQL without auto-complete or execution.

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SQL Interview Questions

SQL Interview Questions

All SQL Questions

Monthly Cohort Retention

Write SQL for top categories and highly active users

Analyze Pirated Theme Usage

Compute Company Suggestion Funnels

Analyze Pirated Theme Usage Impact

Debug ML pipeline and build text parser

Write SQL for seller and vehicle metrics

Top 5 Most Efficient Vehicle Models

Write SQL for TikTok Live creator metrics

Compute early signals for user retention

Debug and harden trial-assignment Python code

Calculate Order Request Metrics

Write SQL for percent and window changes

Find top category by video time spent

Find top-paid employee per department

Compute each member’s current notification status

Compute C/T metrics from bookings and visits

Merge CSVs and build revenue pivot with pandas

Write SQL for geo posting-frequency drops

Train and analyze a classifier

Count weekly customers with ≥$1000 YTD spend

Write SQL for influence score and follower growth

Detect sessions and gaps using SQL LEAD

Analyze member video posting behavior by country

Write SQL window functions for D7 retention

Analyze video flags and reviews with SQL

Write SQL to compute campaign net revenue

Compute CTR drop with exclusions

Find top advertisers and cost per KPI

Parse and build binary data in Python

Transform clickstream with pandas sessionization

Solve SQL and Python OA tasks

Calculate CTR and ad revenue

Write SQL for top drivers and cancellation rates

Write SQL and Python for transaction analytics

Implement vectorized NumPy ops and explain broadcasting

Find top countries by population per continent

Compute article-type diversity per user and histogram

Compute join counts and window ranks

Explain handling very large datasets

Transform and aggregate messy event data

Find recommended friend pairs by shared listening

Analyze shopping funnel with joins and windows

Write SQL for DAU and first-purchase conversion

Write SQL for cuisine median delivery times

Compute monthly signups, conversion, and YoY growth

Reconcile ledgers with SQL/Python and late events

Compare SQL counts, windows, and NULL semantics

Count unconnected posts and reactions

Compute Heavy-Caller Percentages

How to Prepare for SQL Interviews

Master the Core Concepts

Common Patterns You'll See

Practice with Real Company Questions