A self-paced course
From analytics engineer to
data platform engineer.
Learn Spark, Kafka, Flink, open table formats and the streamhouse. You know SQL and dbt; this course builds on that.
How each module works
1. ReadA short lesson: why the tool exists, how it works, how it maps to what you know, and when not to use it.
2. PracticeCoding exercises graded by automated tests, then a quiz.
3. ExplainSay it in your own words and rehearse interview questions.
4. BuildFinish each core track by building a small version of the tool yourself.
Tracks, in order
1 · FND~20 h
Foundations of distributed data
Why this track exists: Spark, Kafka and Flink are three answers to the same few problems: partitioning, replication, ordering, ti…
7 modules
2 · SPK~70 h
Apache Spark
Spark is a general distributed compute engine.
12 modules
3 · LKH~35 h
Lakehouse & open table formats
A table format turns a pile of files in object storage into a database table.
8 modules
4 · JVM~20 h
Java for data engineers
Kafka and Flink are JVM projects.
6 modules
5 · KFK~65 h
Apache Kafka
Kafka is a distributed, replicated, append-only log.
14 modules
6 · FLK~65 h
Apache Flink
Flink is a stateful stream processor.
12 modules
7 · STH~35 h
Streamhouse
Lambda architecture runs two pipelines, batch and streaming, which often disagree.
8 modules