System Design Interview Guide for Data Engineers with Manjinder Brar

Over the years, I’ve sat through dozens of real Data Engineering system design rounds — from ride-sharing scale architectures to real-time fraud detection, customer 360 platforms, clickstream systems, pipelines for ML, and more. I’ve seen exactly what interviewers expect, where candidates fail, and what separates a “good attempt” from a hireable engineer.

After months of research, note-taking, and breaking down FAANG-level interview patterns, I’ve curated this complete ETL System Design Interview Package — a premium, end-to-end guide built from real interview experience, not generic theory.

This is everything you need to dominate your next Data Engineering system design round — whether it’s ETL pipelines, medallion architecture, streaming vs batch decisions, orchestration, scaling strategies, schema evolution, or trade-offs.

Inside this package, you’ll find real-world system design cases, each one structured the way actual interviewers challenge you:

• What clarifying questions to ask

• How to scope the problem like a senior engineer

• How to structure, layer, and defend your architecture

• How to think about data volume, freshness, SLAs, partitions, formats

• How to handle backfills, late-arriving data, schema drift, PII, and GDPR

• How to address cross-questions without getting stuck

• How to articulate trade-offs confidently (the #1 thing interviewers look for)

Each case increases in difficulty, preparing you exactly the way top tech companies test system design maturity — starting from a simple ETL pipeline and scaling up to streaming, multi-layer architectures, identity resolution, fraud detection, recommendation systems, clickstream analytics, and more.

If you’re serious about levelling up your Data Engineering interviews — this is the closest thing to practicing with a real FAANG interviewer.

No fluff. No bootcamp basics.

Just pure, practical, battle-tested knowledge.

Your next Data Engineering system design offer starts here.