Mastering SQL Scenarios for Data Engineering Interviews

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SQL is a critical skill for data engineers, and mastering scenario-based questions can set you apart in interviews. Below are key SQL challenges and solutions, along with practical commands and code snippets to help you prepare.

Common SQL Scenarios & Solutions

1. Calculating Rolling Averages Over 7 Days

SELECT 
date, 
sales, 
AVG(sales) OVER (ORDER BY date ROWS BETWEEN 6 PRECEDING AND CURRENT ROW) AS rolling_avg 
FROM sales_data;

2. Finding Employees with Tenure Below Average

SELECT employee_id, name, tenure 
FROM employees 
WHERE tenure < (SELECT AVG(tenure) FROM employees);

3. Detecting Data Gaps for Products

WITH date_range AS ( 
SELECT generate_series( 
MIN(date), 
MAX(date), 
INTERVAL '1 day' 
)::date AS missing_date 
FROM product_data 
) 
SELECT d.missing_date 
FROM date_range d 
LEFT JOIN product_data p ON d.missing_date = p.date 
WHERE p.date IS NULL;

4. Identifying Customers with Consecutive Monthly Purchases

SELECT customer_id 
FROM ( 
SELECT 
customer_id, 
LAG(purchase_date, 1) OVER (PARTITION BY customer_id ORDER BY purchase_date) AS prev_purchase 
FROM purchases 
) 
WHERE EXTRACT(MONTH FROM purchase_date) - EXTRACT(MONTH FROM prev_purchase) = 1;

5. Calculating Sales Growth Across Quarters

SELECT 
quarter, 
sales, 
(sales - LAG(sales, 1) OVER (ORDER BY quarter)) / LAG(sales, 1) OVER (ORDER BY quarter)  100 AS growth_percentage 
FROM quarterly_sales;

You Should Know: Essential SQL & Data Engineering Commands

Linux Commands for Data Engineers

 Monitor running SQL queries in PostgreSQL 
pg_top -U postgres

Export query results to CSV 
psql -U user -d db -c "SELECT  FROM table" -o output.csv

Process large files efficiently 
awk -F ',' '{print $1,$3}' data.csv > filtered_data.csv

Windows PowerShell for SQL & Data Tasks

 Export SQL Server table to CSV 
Invoke-Sqlcmd -Query "SELECT  FROM Employees" -ServerInstance "SERVER" | Export-Csv -Path "employees.csv"

Bulk insert CSV into SQL Server 
bcp Database.dbo.Table IN "data.csv" -c -T -S ServerName

Optimizing SQL Performance

-- Create indexes for faster queries 
CREATE INDEX idx_customer_id ON purchases(customer_id);

-- Analyze query performance 
EXPLAIN ANALYZE SELECT  FROM large_table WHERE condition;

What Undercode Say

SQL remains a foundational skill for data engineers, and mastering these scenarios ensures you can handle real-world data challenges. Practice these queries, optimize them, and use Linux/Windows commands to streamline workflows.

Prediction

As data complexity grows, SQL optimization and automation (via scripting) will become even more critical in data engineering roles.

Expected Output:

  • Efficient SQL queries for interviews
  • Practical Linux & Windows commands for data tasks
  • Performance optimization techniques

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