Most tutorials show you a CREATE TABLE and call it a lakehouse. This course takes you all the way: the spec internals, every major catalog, all the write and read engines, and the production discipline that separates a weekend pilot from a platform 200 engineers depend on.
Across 23 modules and 116 lessons (~12.5 hours), you’ll follow Sarah — a Head of Data Platform running shared Iceberg storage across three continents — as she makes the decisions you’ll soon make yourself. You’ll read the spec as a working mental model (manifests, snapshots, metadata.json, the commit protocol), then choose a catalog with a real Decision Spine matrix comparing Polaris, Unity OSS, Nessie, Glue, and Hive Metastore — and defend the choice.
From there you build: a complete medallion lakehouse with Kafka CDC into bronze, Spark MERGE plus write-audit-publish into silver, and multi-engine readers (Trino, Snowflake, DuckDB) on gold. You’ll run the maintenance nobody teaches — compaction, expire-snapshots, orphan cleanup, rewrite-manifests — with real cost numbers, and master branching, tagging, and time-travel rollback patterns that auditors and SREs sign off on.
