Bikes Before Rush Hour

A hard Pipeline Design interview practice problem on DataDriven. Write and execute real pipeline design code with instant grading.

Domain

Pipeline Design

Difficulty

hard

Seniority

L5

Problem

We run a bike-share network across dozens of cities and forecast bike demand at each station every hour so operations can pre-position bikes before rush hour. Trip history lands once a day as files from several city operators in different schemas, and each hourly forecast depends on scheduling those daily files through ingest, cleaning, and feature build before it runs, while dock availability streams in continuously and must stay fresh within minutes for the supply signal to hold. Design the pipeline from raw ingestion to a model-ready feature store, keeping the roughly two percent of corrupt trip records (negative durations, zero-distance test rides) out of the features while retaining them in the raw layer.

Summary

Bikes in, bikes out. The city needs to predict demand.

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