Complete DBT(Data Build Tool) Data Transformation Masterclass

The Complete dbt Data Transformation Masterclass is a comprehensive, hands-on course designed to help learners master dbt (Data Build Tool), one of the most widely adopted tools for modern data transformation and analytics engineering. The course covers everything from the fundamentals of dbt to advanced implementation techniques used in enterprise data platforms.

Participants will learn how to build scalable, modular, and maintainable data transformation pipelines using SQL and Jinja, implement data quality tests, create reusable models and macros, manage dependencies, and automate workflows with dbt Core and dbt Cloud. The course also explores best practices for version control, documentation, CI/CD integration, and deployment in production environments.

Through real-world projects and practical labs, learners will gain experience integrating dbt with modern cloud data warehouses such as Snowflake, PostgreSQL, BigQuery, Redshift, and Databricks. The curriculum also introduces analytics engineering concepts, dimensional modeling, incremental loading, snapshots, seeds, sources, and orchestration with Apache Airflow.

By the end of the course, participants will be able to design and manage end-to-end transformation workflows, implement industry best practices, and confidently use dbt in modern data engineering and analytics projects.

What You'll Learn

• Understand Analytics Engineering and the role of dbt
• Install and configure dbt Core and dbt Cloud
• Build modular SQL models using Jinja templating
• Create sources, seeds, snapshots, and incremental models
• Implement data quality testing and documentation
• Develop reusable macros and packages
• Build production-ready dbt projects
• Integrate dbt with Snowflake, BigQuery, Redshift, PostgreSQL, and Databricks
• Orchestrate dbt workflows using Apache Airflow
• Apply Git-based version control and CI/CD practices
• Optimize dbt projects for performance and maintainability

Who Should Attend

• Data Engineers
• Analytics Engineers
• Data Analysts
• BI Developers
• ETL Developers
• SQL Developers
• Cloud Data Engineers
• Database Professionals
• Software Engineers working with data platforms
• Students and professionals transitioning into Data Engineering

Prerequisites

• Basic SQL knowledge
• Familiarity with relational databases
• Basic understanding of data warehousing concepts is helpful but not mandatory

Course Outcome

After completing this course, learners will be able to build, test, document, deploy, and maintain enterprise-grade data transformation pipelines using dbt. They will also be prepared to contribute to modern analytics engineering projects and work effectively with cloud-based data platforms in production environments.