FAANG Cram

40 hard problems across SQL, Python, data modeling, and pipeline architecture. No warmups.

This prep plan is 40 curated data engineering interview problems grouped for structured practice. Each challenge runs real code against live databases or executes Python in a sandboxed environment. You get instant feedback, company tier filtering, seniority calibration, and spaced repetition that keeps weak concepts in rotation until they stick.

How to Use This Plan

Start with the easier items to build pattern recognition for the domain.
Move to medium and hard challenges once you can solve easy ones without hints.
After solving a challenge, read the AI discussion phase prompts to pressure-test your solution.
Track your readiness score on your profile and retry items where you struggled.
When you feel ready, launch a full mock interview at /interview for end-to-end simulation.

SQL Challenges (10)

Who Stayed - hard - Day after day after day. Who kept coming back?
Yesterday's Crown - hard - Every dawn inherits the spending of the day before.
Quarters Apart - hard - Latency trending up or down? The quarters have the answer.
Campaign Conversion Window - hard - A narrow window between impression and action.
Chain of Command - hard - The tree runs deep. Trace every branch back to the top.
The Ninety-Day Comeback - hard - Everyone shows up once. Who comes back before the quarter ends?
The Org Chart in Numbers - hard - Headcount by department, sliced by quarter. Every seat accounted for.
Balance of Arms - hard - Every test has two sides. Count who actually landed on each.
The Path Not Taken - hard - Some found the new path without ever walking the old one.
Then and Now - hard - Accuracy used to be higher.

Python Challenges (10)

Downstream - hard - Nothing runs until what it needs has run.
The Throttle Wall - hard - Stop the abusers. Let the rest through.
Against the Current - hard - Too big to load. Read what you can.
What the Night Changed - hard - Two photographs of the same table, a day apart. Account for everything that moved.
The Stream Joiner - hard - Events don't wait for each other. This does.
Where the Buck Stops - hard - A pile of reporting lines, no order to them. Somewhere in the bag sits the one with no boss.
Out of Nowhere - hard - Every stream has a rhythm. Find the readings that break it.
No Vacancy - hard - Every booking needs a room. Find the busiest moment.
Moving Day - hard - Old schema in, new schema out.
The Output Peak - hard - One stretch outpaced all the others.

Data Modeling Challenges (10)

The Long Route - hard - A package splits, reroutes, and (maybe) arrives.
Financial Trading Warehouse - hard - Every trade, every tick, every fraction of a share. The regulators want receipts.
Insurance Claims Lifecycle - hard - A claim gets filed. Then it gets complicated. Then it gets reassigned. Then it loops back.
Property Booking Platform - hard - Five-star listing. Three-star reality.
The Customer Who Changed - hard - She moved. She upgraded. She became someone new. The record has to keep up.
Telecom Network Connectivity Warehouse - hard - One device goes down. The ripple keeps going.
Online Marketplace - Seller Payouts - hard - The buyer paid one number. The seller got a different one.
Trees Within Trees - hard - A file is also a folder. A folder is also a file.
Three-Sided Marketplace Delivery Schema - hard - One order. Two deliveries. Revenue counted twice. Where is the bug in your schema?
Metric Definition Reverse Engineering - hard - Five numbers on a dashboard. Your job: figure out where they come from.

Pipeline Architecture Challenges (10)

Score It Before It Clears - hard - The fraudsters move fast. Your pipeline has to move faster.
Replicate It Without Breaking It - hard - The source changed. The lake needs to know immediately.
A Stream All Day and a File at Midnight - hard - Real-time and batch. Same pipeline. No compromises.
Event System for Multiple Consumers - hard - One event, many hungry consumers.
One Earthquake, Ten Thousand Tweets - hard - The firehose is on. Separate signal from noise.
Prove the Number Is Right - hard - Bad data in fintech is not just messy. It is expensive.
Three Regions, One Finance Team - hard - Payments from everywhere. One consistent report.
The Models Going Stale - hard - The model is only as good as what you feed it.
Live Viewers, Live Billing - hard - The stream is live. The data cannot wait.
Two Years of Every Click - hard - Every click, every aisle, every day for two years.