🎯 MAANG Data Engineering: Exclusive Technical Interview Prep Set #2

Thank you for being a subscriber to the Elite Career Accelerator! Your commitment to upskilling and growing your data engineering career is what sets you apart.

Welcome back, Elite members! You crushed Set 1 of the Maang Data Engineering interview prep, and now it's time to level up with Set 2—SQL and Python questions straight from real-world interviews.

If you thought Set 1 was intense, get ready. This round tests your edge cases, problem-solving skills, and real-world data handling abilities. Let's go! 🔥

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🚀 Not an Elite Member Yet? You’re missing out on exclusive first-hand Questions from real candidates. Get access to the full Set 2 deep-dive including:

✅ SQL & Python questions used in real MAANG Technical interviews

✅ Schema walkthroughs & hands-on challenges

✅ Insider hiring process breakdowns

✅ Meta’s Onsite Interview strategy and questions (coming up next!)

🔒 Upgrade now to unlock full access! →

📌 SQL Schema

products                              sales
+------------------+---------+        +------------------+---------+
| product_id       | int     |------->| product_id       | int     |
| product_class_id | int     |  +---->| store_id         | int     |
| brand_name       | varchar |  |  +->| customer_id      | int     |
| product_name     | varchar |  |  |  | promotion_id     | int     |
| price            | int     |  |  |  | store_sales      | decimal |
+------------------+---------+  |  |  | store_cost       | decimal |
                                |  |  | units_sold       | decimal |
                                |  |  | transaction_date | date    |
                                |  |  +------------------+---------+
                                |  |
stores                          |  |  customers
+-------------------+---------+ |  |  +---------------------+---------+
| store_id          | int     |-+  +--| customer_id         | int     |
| type              | varchar |       | first_name          | varchar |
| name              | varchar |       | last_name           | varchar |
| state             | varchar |       | state               | varchar |
| first_opened_date | datetime|       | birthdate           | date    |
| last_remodel_date | datetime|       | education           | varchar |
| area_sqft         | int     |       | gender              | varchar |
+-------------------+---------+       | date_account_opened | date    |
                                      +---------------------+---------+

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📌 SQL Challenges: Real Interview Scenarios

1️⃣ Find Unsold Products

How many products have never been sold?

✅ Expected Output:

+----------------+
| count_products |
+----------------+
|            352 |
+----------------+

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