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

Calculate Order Request Metrics

Count unconnected posts and reactions

Write SQL for reply-based recipient metrics

Analyze Pirated Theme Usage Impact

Compute ad impression conversion rates

Write SQL for repeat churn

Query departments and top earners

Compute a Seven-Day Rolling Average

Calculate Cohort Retention

Analyze spend cohort and source shifts

Compute churn with re-subscriptions

Write SQL for call metrics

Find high-value crypto users and top CTR

Compute High-Call Usage Rates

Compute Cohort Retention Rate

Explain Pandas and SQL Basics

Find Top-5 Similar Rows

Analyze advertiser spend by source

Write SQL for multi-account metrics

Count Recent High-Volume Call Users

Analyze Restaurant Customer Metrics

Handle repeated churn in SQL

Calculate Pirated Usage and Revenue Loss

Find least active countries

Differentiate pandas objects and SQL filters

Count heavy callers in 7 days

Find high-value crypto users and top-CTR product

Implement vectorized NumPy ops and explain broadcasting

Write SQL using HAVING and window functions

Find top advertisers and cost per KPI

Clean and Merge Housing Data

Write SQL for call pickup and usage metrics

Debug and harden trial-assignment Python code

Write SQL for percent and window changes

Use pandas to aggregate, pivot, and label

Compute Ride Metrics in SQL

Pivot daily users and revenue by platform

Write SQL for seller and category metrics

Write SQL for top categories and highly active users

Compute article-type diversity per user and histogram

Compute this-year spend share of last-year whales

Find Lowest Prices for Highly Rated Categories

Debug row loss after SQL joins

Write SQL to compute signup and retention lift

Write SQL and Python for transaction analytics

Write SQL for seller and vehicle metrics

Write SQL for CTR and Revenue

Write SQL for call analytics

Clean scores and return top 5 students

Find multi-account buckets and unread rate

How to Prepare for SQL Interviews

Master the Core Concepts

Common Patterns You'll See

Practice with Real Company Questions