Key SQL Questions in Data Science Interviews
✅ Why SQL Matters in Data Science Interviews
SQL is essential for:
Data extraction from databases
Data wrangling before analysis/modeling
Business analytics and dashboards
Collaborating with data engineers and product managers
You’re expected to be fluent in writing, reading, and optimizing SQL queries.
🟢 Basic SQL Questions
These test your fundamentals:
SELECT, FROM, WHERE
“Retrieve all customers from the US.”
ORDER BY
“List top 10 most expensive products.”
LIMIT
“Show only the first 5 rows of the result.”
DISTINCT
“How many unique users visited the site?”
Aliases (AS)
“Rename columns in your result.”
Basic filtering with logical operators
WHERE age > 25 AND country = 'USA'
🟡 Intermediate SQL Questions
These involve joins, aggregation, and grouping.
JOINs (INNER, LEFT, RIGHT, FULL)
“List users and their orders (even if some users placed no orders).”
GROUP BY + Aggregations
“Find the average purchase value per user.”
HAVING clause
“List users who made more than 5 purchases.”
CASE statements
“Classify users as ‘high’, ‘medium’, or ‘low’ spenders.”
Subqueries (IN, EXISTS, SELECT in WHERE/SELECT)
“Find users who bought more than the average amount.”
NULL handling
“Count how many users have no email address.”
🔴 Advanced SQL Questions
These test your logic, problem-solving, and optimization skills.
Window Functions (OVER, PARTITION BY, ROW_NUMBER, RANK)
“Find the second highest salary in each department.”
CTEs (WITH clauses)
“Use common table expressions for readable multi-step queries.”
Self-Joins
“Find managers and their direct reports.”
Date Functions
“Calculate monthly active users (MAUs).”
LEAD / LAG
“Compare each order with the previous one.”
Percentiles & Median
Not natively supported in all SQL engines — often asked to write custom logic.
Nested subqueries
“Find products that were sold more than any product in category X.”
🧠 Business-Focused SQL Case Questions
These simulate real data science scenarios:
Churn Rate Calculation
“What’s the monthly churn rate for users?”
User Funnel Conversion
“Out of users who visited the homepage, how many ended up purchasing?”
Retention Cohort Analysis
“Track user retention over weeks after signup.”
A/B Test Metrics
“Compare conversion rate between control and treatment groups.”
Revenue or LTV Analysis
“Calculate customer lifetime value (LTV) by cohort.”
🔍 Tips to Ace SQL Interviews
Understand the data schema. Ask clarifying questions.
Think out loud. Interviewers value your process.
Start simple, then optimize. Write a working query first.
Avoid hardcoding. Use dynamic logic (e.g. CURRENT_DATE, not '2023-01-01').
Check for edge cases. Nulls, duplicates, missing joins.
📚 Practice Resources
LeetCode SQL Questions
StrataScratch
Mode Analytics SQL Tutorial
SQLZoo
DataLemur
Would you like:
A mock SQL interview question and solution?
SQL questions by company (e.g. Amazon, Facebook)?
A custom SQL study plan?
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The STAR Method for Answering Behavioral Interview Questions
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