Building Modular and Testable Data Pipelines with dbt on Databricks

Modern data teams need reliable, version-controlled, and thoroughly tested pipelines to transform raw data into actionable insights. Managing these workflows at scale requires combining the processing power of Databricks with the structured transformation framework of dbt. This course teaches you how to design and maintain clean data architectures that scale seamlessly. In this course, you will learn how to build production-grade data transformation pipelines from scratch. You will transition from writing raw, unorganized SQL to developing modular, reusable, and fully tested data models using both dbt Core and dbt Cloud on Databricks. What you'll learn: - Understand the foundational concepts of dbt, including project structure, configuration with YAML, and the multi-layer Bronze-Silver-Gold data architecture. - Configure dbt to connect seamlessly with Databricks using both dbt Cloud and dbt Core environments. - Build modular data models using SQL, Jinja templating, and custom macros to write dry, reusable transformation logic. - Implement robust data quality checks using modern dbt testing configurations and third-party utility packages. - Apply advanced materialization strategies, including incremental loads and snapshots, to optimize pipeline performance and track historical changes. - Integrate version control best practices to collaborate safely and maintain a clean history of your data pipeline changes. You will start with core data engineering concepts and dbt setup before moving step-by-step through modeling, testing, and advanced performance tuning. The written explanations and practical code snippets guide you from initial project initialization to deploying a resilient, production-ready pipeline. This course is designed for aspiring data engineers, analytics engineers, and data analysts who want to build structured data pipelines. No prior experience with dbt or Databricks is required, though a basic understanding of SQL is helpful. Start building cleaner, more reliable data pipelines today.