Data Nerds! I just launched a free course on "SQL for Data Engineering!"
This is the course I wish I had when I stopped asking “how do I query this?” and started asking “how do I build this?” 🏗
This YouTube video has over 14 hours of content and walks through building a real data warehouse and production-ready SQL pipeline from scratch.
We go far beyond SELECT statements:
1️⃣ Production SQL — DDL, DML, CTEs, subqueries, window functions, and advanced query patterns
2️⃣ Data Modeling — Designing star schemas and analytics-ready warehouse tables
3️⃣ Data Warehousing — Structuring fact and dimension tables properly
4️⃣ End-to-End Pipelines — Transforming raw data into clean, production-ready outputs
5️⃣ Engineering Workflow — Using Terminal, DuckDB, VS Code, and Git
And because the best way to learn is to build, we complete two real projects:
📊 Project #1 — Exploratory Data Analysis on a live warehouse dataset
🏗 Project #2 — Build a full SQL-based data pipeline
Huge thank you to the team that made this possible:
Kelly Adams - Course Producer
Rikki Singh - Content Developer
Brannon Linder - Video Editor
P.S. If you’re wondering how this compares to my SQL for Data Analytics course:
That course focuses on querying data to answer business questions.
This one focuses on modeling data, designing warehouse schemas, writing production-grade SQL, and building end-to-end pipelines using the Terminal and Git.
🧑💻 Analytics is about extracting insights.
🧑🔧 Engineering is about building the systems that make those insights possible.
Neither course is a prerequisite, but they prepare you for different roles.
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