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Practice Databricks coding skills with hands-on exercises. Import into Databricks Free Edition, write code, run assertions, check pass/fail. Covers Delta Lake, Spark SQL, PySpark, Auto Loader, medallion architecture, window functions, and more.
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149 exercises, 4 production-grade pipeline labs, and 2 deep-dives. All on Databricks Free Edition.
Clone once, import into Databricks, pick a folder. Exercises fail loud until your code is right; labs ship with synthetic data so you build production-style pipelines, not toy ones.
Jakub Lasak - Databricks Data Engineer. Helping you interview like seniors, execute like seniors, and think like seniors.
Prepping for interviews? Writing code is one half of the battle - knowing the questions that actually come up is the other. I maintain Databricks Interview Cheat Sheets by seniority level (junior / mid / senior / bundle).
Fluency comes from reps, not reading. Three structured paths:
exercises/ - focused reps on a single concept. LeetCode-style, 5-30 min each.pipeline-labs/ - end-to-end medallion pipelines on a business scenario. 2-3 hours each.deep-dives/ - go deep on a single topic, hands-on, end to end. 1-3 hours each.| Exercises | Pipeline Labs | Deep-Dives | |
|---|---|---|---|
| Format | Single notebook, one TODO per exercise | Multi-notebook guided project | Single-topic deep investigation |
| Time | 5-30 min per exercise | 2-3 hours per lab | 1-3 hours |
| Scope |
| One concept (MERGE, window functions, ...) |
| End-to-end project (ingestion -> bronze -> silver -> gold) |
| One topic, hands-on in depth |
| Narrative | None. "Given table X, write..." | Business scenario. "You're building a streaming pipeline for..." | Focused. "Go deep on one topic, end to end." |
| Order | Pick any, skip around | Sequential notebooks that build on each other | Sequential; each step layers on the last |
| Goal | Drill a skill until it's automatic | See how concepts fit in a real project | Build real, hands-on command of one topic |
exercises/)| Topic | Notebooks | Exercises | Description |
|---|---|---|---|
| Delta Lake | 6 | 51 | MERGE operations, time travel, schema enforcement, OPTIMIZE, liquid clustering, change data feed |
| ELT | 7 | 53 | Spark SQL joins, window functions, PySpark transformations, Auto Loader, batch ingestion, medallion architecture, complex data types |
| Streaming | 6 | 45 | Structured Streaming basics, windowed aggregations & watermarks, stream-static joins, stream-stream joins, foreachBatch patterns, checkpointing & recovery |
Total: 19 notebooks, 149 exercises
More exercise topics coming - next up: Unity Catalog, Performance, and DLT.
pipeline-labs/)Multi-notebook, end-to-end medallion pipelines with a business scenario. Each runs 2-3 hours and ships with a synthetic data generator.
| Lab | What You Build | Focus |
|---|---|---|
| Apparel Retail 360 (DLT) | End-to-end retail analytics pipeline on Delta Live Tables with a full medallion architecture. | DLT, Medallion, SCD Type 2, Streaming, Data Quality Expectations |
| Fintech Transaction Monitoring | Real-time fraud-monitoring pipeline for a payment processor handling 500K+ transactions/day. | Structured Streaming, Rescued Data, Watermarked Dedup, Stream-Static Joins, Liquid Clustering |
| DE Associate Certification Prep | Production-grade pipeline covering every exam domain of the Databricks Data Engineer Associate cert. | Auto Loader, COPY INTO, Medallion, SCD2, Jobs, Unity Catalog |
| PySpark Developer Cert Prep | E-commerce analytics pipeline covering every domain of the Spark Developer Associate cert. | DataFrame API, Structured Streaming, Data Skew, Performance Tuning |
deep-dives/)Single-topic labs that go deep on one technique or capability - hands-on, end to end.
| Lab | What You Build | Focus |
|---|---|---|
| 6 Delta Optimization Techniques | Iteratively apply and measure core Delta performance levers on a synthetic 50M-row dataset. | Partitioning, Z-Order, OPTIMIZE, Auto Optimize, Liquid Clustering, VACUUM |
| Build a Genie Space | Stand up and tune a production Databricks Genie space on a retail star schema, then benchmark its natural-language answer accuracy against ground-truth SQL. | Genie, Unity Catalog Functions, Star Schema, Benchmarking, AI/BI Dashboards |
Everything runs on Free Edition: serverless compute, Unity Catalog, Delta Lake. No cloud account, no cluster config.
New exercises and labs ship regularly. Follow on LinkedIn or subscribe to the Substack newsletter to be notified when new content drops.
Found a bug? Have a suggestion? Open an issue.
Disclaimer: This is an independent educational resource created by Jakub Lasak. Not affiliated with, endorsed by, or sponsored by Databricks, Inc. "Databricks" and "Delta Lake" are trademarks of their respective owners.