🚀 SQL Interview Challenges: Data Engineer & Data Analyst

Welcome to my SQL Practice Repository! This repository contains my solutions to real-world SQL interview questions from top tech companies. I use these challenges to sharpen my data manipulation, aggregation, and analytical skills.

🏢 Companies Included

I have solved data scenarios based on business cases from:

• Airbnb: Pricing strategies and host earnings analysis.
• Amazon (Prime Video): Content engagement and viewership tracking.
• LinkedIn: User engagement scoring and content type performance.
• Meta: Ad performance, custom audiences, and cost per conversion.
• Microsoft (Teams): Data security, file sharing, and risk identification.
• Stripe: Loan repayment success rates and business revenue variability.

🛠️ Key SQL Skills Demonstrated

In these scripts, I have applied advanced SQL techniques to solve complex business logic, including:

• CTEs (Common Table Expressions): Structuring complex multi-step queries for readability.
• Window Functions: Using PERCENT_RANK() OVER() for percentile calculations.
• Conditional Aggregation: Utilizing SUM(CASE WHEN ...) and AVG(CASE WHEN ...) for pivoting and targeted metrics.
• String Manipulation: Applying SPLIT_PART() and concatenations (||) to clean and extract text data.
• Date & Time Filtering: Using EXTRACT(), BETWEEN, and date logic to analyze time-series data.
• Complex Joins & Aggregations: Joining Fact and Dimension tables (fct_ and dim_) to generate meaningful business insights.

📂 Repository Structure

The SQL files are organized by company name. Inside each file, you will find the business question as a comment, followed by the optimized SQL query.

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Disclaimer: All questions are sourced from interviewmaster.ai. Solutions are written by me as part of my continuous learning journey.