10 Critical SQL Queries to Ace Any Data Job Interview

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Introduction: Why SQL Mastery Matters in Data Interviews

Suppose you are applying for the job of Data Analyst, BI developer or Backend Engineer. In that case, you have to face SQL-based problem-solving questions. SQL is the foundation of data manipulation and reporting, and interviewers often assess your ability to write clear, efficient queries to extract insights from data. This guide covers 10 critical SQL queries that frequently appear in interviews, with realistic examples using SQL Server syntax. Practice these, and you’ll walk into your interview with confidence.

1. SELECT with WHERE and Logical Operators

Scenario: Filter customer data by region and activity status.

Table: Customers

CustomerID	Name	Region	Active
1	Alice	East	1
2	Bob	West	0

SELECT Name, Region
FROM Customers
WHERE Region = 'East' AND Active = 1;

Output:

Name	Region
Alice	East

👉 Why it matters: Shows basic filtering logic—used in nearly every SQL task.

2. JOINs (INNER, LEFT)

Scenario: Match orders to customers.

Tables: Customers, Orders

SELECT C.Name, O.OrderDate
FROM Customers C
INNER JOIN Orders O ON C.CustomerID = O.CustomerID;

LEFT JOIN Example:

SELECT C.Name, O.OrderDate
FROM Customers C
LEFT JOIN Orders O ON C.CustomerID = O.CustomerID;

👉 Why it matters: JOINs test your understanding of data relationships, crucial for normalized databases.

3. GROUP BY with HAVING

Scenario: Find products with more than 10 orders.

Table: Orders

SELECT ProductID, COUNT(*) AS TotalOrders
FROM Orders
GROUP BY ProductID
HAVING COUNT(*) > 10;

Output:

ProductID	TotalOrders
101	12

👉 Why it matters: HAVING filters groups—interviewers love to test this subtle distinction from WHERE.

4. Subqueries

Scenario: Find customers who made more orders than the average.

SELECT CustomerID
FROM Orders
GROUP BY CustomerID
HAVING COUNT(*) > (
    SELECT AVG(OrderCount)
    FROM (
        SELECT CustomerID, COUNT(*) AS OrderCount
        FROM Orders
        GROUP BY CustomerID
    ) AS AvgOrders
);

👉 Why it matters: Subqueries test logical thinking and multi-layered filtering.

5. Window Functions (ROW_NUMBER, RANK)

Scenario: Get the latest order per customer.

SELECT *
FROM (
    SELECT *, ROW_NUMBER() OVER (PARTITION BY CustomerID ORDER BY OrderDate DESC) AS rn
    FROM Orders
) AS Ranked
WHERE rn = 1;

Output:

CustomerID	OrderID	OrderDate	rn
1	102	2024-12-01	1

👉 Why it matters: These functions are used in ranking, deduplication, and pagination.

6. Common Table Expressions (CTEs)

Scenario: Break a query into readable parts.

WITH HighValueOrders AS (
    SELECT OrderID, TotalAmount
    FROM Orders
    WHERE TotalAmount > 1000
)
SELECT * FROM HighValueOrders;

👉 Why it matters: CTEs improve readability and modularity, showing you’re thinking like a developer.

7. Aggregations (SUM, COUNT, AVG)

Scenario: Analyze monthly sales.

SELECT MONTH(OrderDate) AS Month, SUM(TotalAmount) AS Revenue
FROM Orders
GROUP BY MONTH(OrderDate);

Output:

Month	Revenue
1	5000

👉 Why it matters: These aggregations are bread-and-butter for reporting and dashboards.

8. CASE Statements

Scenario: Categorize customers by total spend.

SELECT CustomerID,
       SUM(TotalAmount) AS TotalSpent,
       CASE 
           WHEN SUM(TotalAmount) > 5000 THEN 'High'
           WHEN SUM(TotalAmount) BETWEEN 2000 AND 5000 THEN 'Medium'
           ELSE 'Low'
       END AS Category
FROM Orders
GROUP BY CustomerID;

Output:

CustomerID	TotalSpent	Category
3	6500	High

👉 Why it matters: CASE is a powerful tool for conditional logic in SQL.

9. UPDATE with JOIN

Scenario: Activate all users who placed an order.

UPDATE C
SET C.Active = 1
FROM Customers C
INNER JOIN Orders O ON C.CustomerID = O.CustomerID;

👉 Why it matters: Tests your understanding of UPDATE with JOINs, a common real-world task.

10. DELETE with Conditions

Scenario: Delete test accounts (where the email ends with @test.com)

DELETE FROM Customers
WHERE Email LIKE '%@test.com';

👉 Why it matters: DELETEs must be precise to avoid data loss—interviewers want to see caution and logic.

✅ Conclusion: Master These Queries to Stand Out

Interviewers don’t just test if you know SQL—they want to see if you can solve real-world data problems under pressure.

These 10 critical SQL queries cover the most important concepts:

Data filtering and transformation
Table relationships
Grouping and aggregations
Ranking and conditional logic
Data modification with care

Practice each one in SQL Server Management Studio (SSMS) or online tools like SQL Fiddle or Mode Analytics.

🚀 Final Tip:

When you’re in the interview, don’t just write the query. Explain your thought process clearly—it’s often more important than the final output.

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