Data Nerds! This repo contains all the files needed to follow along my free course: dbt for Data Analysts & Engineers
🙋🏼♂️ Course Leader: Luke Barousse
📺 Video Editor: Brannon Linder
You already know SQL. This course teaches you to turn scattered SQL scripts into a tested, documented, version-controlled data pipeline with dbt. It's the T in ELT: data engineers extract and load the raw data (that part already happened); analytics engineers transform it inside the warehouse. That's the job this course trains.
You'll build two portfolio projects: a local, tested, automated job-market pipeline on DuckDB (published with GitHub Actions), then a production-grade rebuild on Databricks — a year of real job postings (~692k rows) from raw files to a documented star schema.
Lesson notes live in the course itself — this repo holds the code:
| Folder | What it is |
|---|---|
| project_1/ | Reference implementation of Project #1 (dbt + DuckDB, the finished repo you build in the course) |
| project_2/ | Reference implementation of Project #2 (dbt + Databricks) |
project_*/snippets/ |
Files the videos hand out via lukeb.co short links, frozen at the lesson that uses them |
| project_2/bonus/ | Extra SQL and YAML beyond the videos; dbt never reads it |
| docs/ | The published dbt docs sites for both projects (GitHub Pages) |
| resources/ | Diagrams and images used in the videos |
| img/ | Images used in the READMEs |
Each project folder is self-contained with its own uv environment and a single dbt install (dbt v2 bundles the DuckDB and Databricks adapters).
Requires uv (Part 1 of the bootcamp covers it). In the course you build your own repo from scratch — to run a reference project directly:
git clone https://github.com/lukebarousse/dbt_Analytics_Engineering_Course.git
cd dbt_Analytics_Engineering_Course/project_1
python scripts/download_data.py # downloads the course dataset (~85MB) into project_1/data/
uv sync # per-project env: dbt + DuckDB adapter
cd analytics && uv run dbt debug # verify everything worksA year of real job postings (Data Engineer, Data Analyst, Data Scientist roles) collected by my datanerd.tech pipeline, July 2025 - June 2026. Raw and intentionally messy: duplicate scrapes, error rows, salary as text, dates like "10 hours ago", JSON columns. Cleaning it is the course.
Files ship as monthly parquet in the dataset release; the download script above fetches them for you.