Data Engineering
Pipelines, ETL/ELT, batch vs streaming, and moving data reliably at scale.
What you'll actually learn
Moving data reliably at scale is a different problem than querying it once it's already sitting in a database — this track covers the actual machinery: pipelines that extract, transform, and load data from one system into another, the real tradeoffs between batch processing (run it every night) and streaming (process it as it arrives), and what actually breaks when a pipeline that worked fine at a thousand rows meets ten million.
What you'll be able to do
You'll build a real pipeline that moves data from a raw source through transformation into a usable destination, and you'll be able to explain — from experience, not theory — exactly when batch is the right call and when it isn't. That's the judgment call that separates someone who can write a SQL query from someone who can be handed "make this data pipeline not fall over."
Syllabus
Frequently asked
Roughly 1 hour across 8 hands-on quests — you can go at your own pace and pick up exactly where you left off.
You should be comfortable with Python, SQL in Practice first — the skill tree unlocks Data Engineering once you've cleared those.
Yes — Data Engineering is fully available on the free tier, starting with a free first quest and no payment method required to sign up. Plus and Elite remove pacing limits but don't gate any of the Data Engineering curriculum behind a paywall.
Create a free account and begin your first quest — no card required.
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