Warehouse Modeling (dbt)

GitHub repo + live demo/Colab + README + metrics report

Stack: Python, Spark, Airflow, Kafka, dbt, cloud

• Works as specified30

  Every feature in the brief runs end to end with real data, and the reviewer can follow the README to try it.

• Code quality & design20

  Clear structure, sensible names, input validation, no secrets in the repo, and a short note on the main design choices.

• Testing & evidence20

  Automated tests for the core paths, plus a live URL, screenshots or a short demo video.

• Documentation15

  README covers purpose, setup, how to run tests, and known limits.

• Reasoning & presentation15

  The write-up explains trade-offs and results in plain language, with numbers where they exist.

Pass 60% · Merit 75% · Distinction 90%