FAANG-Style SQL Interview Traps (And How to Avoid Them)

SQL interviews at FAANG (Facebook/Meta, Amazon, Apple, Netflix, Google) are not about syntax. They are designed to test logical thinking, edge cases, execution order, and data correctness at scale. Many strong candidates fail—not because they don’t know SQL, but because they fall into subtle traps.

In this blog, we’ll walk through real FAANG-style SQL traps, why candidates fail them, and how to answer like a senior data engineer or analyst.

1. NOT IN + NULL: The Silent Interview Killer

Question

Find users who never placed an order.

Common (Wrong) Answer

SELECT user_id
FROM users
WHERE user_id NOT IN (
    SELECT user_id FROM orders
);

Why This Fails

If the subquery returns even one NULL, the entire query returns no rows. This is standard SQL behavior—and FAANG interviewers expect you to know it.

FAANG-Safe Answer

SELECT u.user_id
FROM users u
WHERE NOT EXISTS (
    SELECT 1
    FROM orders o
    WHERE o.user_id = u.user_id
);

What they’re testing: NULL handling and logical correctness.

2. Top-N Per Group: Ties Break Offers

Question

Find the top 3 salaries per department.

Trap Answer

ROW_NUMBER() OVER (PARTITION BY dept_id ORDER BY salary DESC)

Why This Fails

ROW_NUMBER() ignores ties. If two employees share the same salary, one gets excluded.

Correct Answer

DENSE_RANK() OVER (PARTITION BY dept_id ORDER BY salary DESC)

What they’re testing: Understanding of ranking functions and edge cases.

3. WHERE vs HAVING: Aggregation Logic

Question

Find users with more than 3 orders in 2024.

Wrong Logic

HAVING COUNT(*) > 3 AND order_date >= '2024-01-01'

Correct Answer

SELECT user_id
FROM orders
WHERE order_date >= '2024-01-01'
GROUP BY user_id
HAVING COUNT(*) > 3;

Key rule:

• WHERE filters rows
• HAVING filters aggregates

4. LEFT JOIN Turned into INNER JOIN

Question

List all users and their last login date (including users who never logged in).

Trap Query

LEFT JOIN logins l ON u.id = l.user_id
WHERE l.login_date >= '2024-01-01'

Why This Fails

The WHERE clause removes NULLs—effectively converting the LEFT JOIN into an INNER JOIN.

Correct Answer

LEFT JOIN logins l
  ON u.id = l.user_id
 AND l.login_date >= '2024-01-01';

What they’re testing: Join behavior and SQL execution order.

5. MAX(date) with Non-Aggregated Columns

Question

Get the latest order for each user.

Wrong Answer

SELECT user_id, MAX(order_date), amount
FROM orders
GROUP BY user_id;

Why This Fails

The amount does not correspond to the max date.

Correct Answer

SELECT user_id, order_date, amount
FROM (
  SELECT *,
         ROW_NUMBER() OVER (
           PARTITION BY user_id
           ORDER BY order_date DESC
         ) rn
  FROM orders
) t
WHERE rn = 1;

What they’re testing: Column correlation and data correctness.

6. Date Filtering Trap (Timestamps)

Question

Fetch orders from January 2024.

Trap

WHERE order_date BETWEEN '2024-01-01' AND '2024-01-31'

Correct Answer

WHERE order_date >= '2024-01-01'
  AND order_date <  '2024-02-01';

Why FAANG cares: Production systems store timestamps, not just dates.

7. DISTINCT Is Not a Band-Aid

Question

Count unique active users per day.

Trap

SELECT DISTINCT date, COUNT(user_id)
FROM events
GROUP BY date;

Correct Answer

SELECT date, COUNT(DISTINCT user_id)
FROM events
GROUP BY date;

What they’re testing: Understanding row-level vs aggregate-level DISTINCT.

8. Window Functions in WHERE Clause

Question

Find users with more than 5 orders.

Trap

WHERE COUNT(*) OVER (PARTITION BY user_id) > 5

Correct Answer

SELECT DISTINCT user_id
FROM (
  SELECT user_id,
         COUNT(*) OVER (PARTITION BY user_id) cnt
  FROM orders
) t
WHERE cnt > 5;

What they’re testing: SQL execution order mastery.

9. Anti-Joins: Correct vs Scalable

Question

Find users with no activity.

Acceptable but Risky

LEFT JOIN events e ON u.id = e.user_id
WHERE e.user_id IS NULL;

FAANG-Preferred

WHERE NOT EXISTS (
  SELECT 1 FROM events e WHERE e.user_id = u.id
);

Why: Better performance and clearer intent at scale.

How FAANG Evaluates SQL Answers

They don’t just look for a working query. They evaluate:

• NULL safety
• Edge-case handling
• Execution order awareness
• Performance at scale
• Clarity of thought

If you explain why your solution is safe, you score higher—even if syntax isn’t perfect.

Final Interview Tip

Before you say “done,” ask yourself:

• What if there are NULLs?
• What if there are ties?
• What if data volume is huge?

That mindset is what FAANG interviews are really testing.