Idempotent ETL Pipeline with Schema Drift
challenge idempotent-etl-pipeline-with-schema-drift
Mid Data Engineer interview. Generate sample CSVs with realistic drift and build a re-runnable pipeline that lands them in a clean table, rejects bad rows with reasons, and traces every row back to source.
- etl
- data-engineering
- pipeline
- idempotency
Start this challenge
Run this in your terminal. You need Node.js 20+ and git.
- The CLI signs you in through the browser if needed and asks which agent you will use: Claude Code, Cursor, or Codex.
- It downloads PROBLEM.md, starter files and tests, sets up a git repo, and starts a 90-minute timer. You see the full problem statement once you start.
- You solve it on your own machine, in your own editor, with your own agent. No browser sandbox.
- When you are done,
npx @kodwai/cli@latest submitpackages your code, git history, test runs, agent transcript, and the time you took, and sends it off to be scored.
How you are scored
Your session gets a score from 0 to 100 across three axes. Most of the weight goes to how you direct the agent, because that is the part a careless prompt cannot fake. Passing the tests matters, but it is not enough on its own. Every signal points to its evidence in your transcript, commits, and test runs, and the score comes with a confidence interval so you can see how certain it is.
Direction
50 ptsHow you steer, verify, and decompose.
Spec Precision · Verification Rigor · Decomposition · Recovery · Intent Fidelity · Engagement
Outcome
35 ptsWhat shipped, replayed and stress-tested to prove it holds.
Tests · Code Quality · Complexity
Lift
15 ptsHow far you beat a solo AI, not just that you passed.
Edge-Case Coverage · Lift over AI
Read how the AI Collaboration Score for coding agents works for every signal and how the axes are weighted.
Try Idempotent ETL Pipeline with Schema Drift with your agent.
Create a free account, then run the command above. Solving challenges, your score, your profile, and the leaderboard are free for developers.