How to Write dbt Macros | 4 Real-World Use Cases Explained

How to write dbt macros — explained with 4 real-world use cases you can start using in your dbt project today. Whether you're using dbt Core or dbt Cloud, dbt macros are the single most powerful feature for writing clean, reusable, production-ready data pipelines. If you're still copy-pasting SQL logic across your dbt models, this dbt macros tutorial will change how you work. dbt macros use Jinja templating to let you write logic once and call it anywhere. What this dbt macros tutorial covers: 00:00 – What are dbt macros and how do they work 00:53 – Use Case 1: Standardizing data transformations (clean string columns the same way across every dbt model) 12:20 – Use Case 2: Enforcing business logic in dbt (build income bucket logic using dbt macros with Jinja) 21:40 – Use Case 3: Environment-specific config in dbt (send data to different databases in dev, staging and prod using dbt macros) 32:25 – Use Case 4: How to write generic tests in the dbt macros directory (reusable dbt tests with zero duplication) 37:45 – How to document dbt macros using properties.yml (dbt macro documentation best practices) Who is this dbt macros tutorial for? Data engineers and analytics engineers who know basic dbt models and want to write scalable, DRY dbt project code using Jinja macros, custom dbt tests, and environment-aware configurations. Why learn dbt macros? dbt macros work like functions in Python — define logic once in your macros directory, call it everywhere. When business logic changes, update one macro file and it propagates to every dbt model instantly. No more hunting through 50 SQL files. 🔔 Subscribe for weekly dbt Core, dbt Cloud, SQL and data engineering tutorials. 👍 If this dbt macros tutorial helped you, a like takes 1 second and helps others find it. 💬 Questions about dbt macros, Jinja, or properties.yml? Drop them below — I reply to every comment. #dbtmacros #dbt #dbtcore #dbtcloud #dataengineering #analyticsengineering #Jinja #SQLtransformation #datapipeline #modernDataStack