Would you voluntarily spend another five hours on this kind of problem? Why?
Data Engineering · 90–120 min
Repair a messy data pipeline
Experience cleaning, contracts, repeatability and data-quality investigation.
Start the experiment01 · Setup
What you need
- Basic Python or SQL.
You may stop when the timebox ends. An incomplete result is still useful evidence.
02 · Task
The work sequence
- 01
Download a small public CSV and profile missing or inconsistent values.
- 02
Create a cleaned table with an explicit schema.
- 03
Make the load idempotent: running twice must not duplicate rows.
- 04
Add three quality checks and a short data dictionary.
03 · Pay attention
Watch your reaction, not only the output
- Did chasing a wrong row feel tedious or detective-like?
- Did you enjoy defining what clean means?
Plot twist
Difficulty does not mean the career is a bad fit. The useful question is whether curiosity returned after the difficulty.
04 · Reflect
Three honest questions
Which part gave you energy, and which part drained it?
What evidence—not a salary video—would you gather before choosing this path?
This site does not save your answers. Put them in your own notebook if useful.
05 · Where to go next