Social Graph SQL & Python Interview Questions
Social networks process engagement at massive scale — posts, likes, follows, shares, and content interactions. These SQL and Python challenges are modeled after work at Meta, LinkedIn, TikTok, Snap, Twitter/X, Reddit, Pinterest, YouTube, Discord, Twitch, and more. Master network effects analysis, viral coefficients, content ranking signals, creator monetization, feed algorithm metrics, and user engagement funnels.
These practice problems are modeled after the kind of data and analytics challenges teams in this industry typically face.
Company names and logos are trademarks of their respective owners, used here only to describe the kind of data these companies work with. Let's Data Science is not affiliated with, endorsed by, or sponsored by any company shown. Practice problems are original works and are not real interview questions from these companies. Rights & takedowns.
Difficulty Distribution
Easy
25
19% of problems
Medium
53
41% of problems
Hard
42
33% of problems
Expert
9
7% of problems
What You'll Practice
Topics Covered
All Problems129 total
Ready to practice Social Graph?
129 SQL and Python challenges built from real social graph data. Graded instantly in your browser — no setup required.