Data Build Tool (dbt) Developer
Learn dbt Developer skills, SQL-based data transformation, data modeling, testing, documentation, analytics engineering, and modern data warehouse development.
Course Description
The Data Build Tool (dbt) Developer Training Program is designed to help learners understand modern analytics engineering and SQL-based data transformation. dbt is widely used by data teams to transform raw data into reliable, structured, and analytics-ready datasets inside cloud data warehouses.
Students will learn dbt architecture, project setup, models, sources, seeds, snapshots, macros, tests, and documentation. The course also covers Jinja templating, incremental models, dependency management, data quality testing, and workflow execution.
Learners will gain hands-on experience in building modular SQL transformations, creating reusable data models, implementing data validation tests, and developing end-to-end analytics workflows.
Trainer
N
Navdeep Singh
Data Analytics and Enterprise Data Architecture
20 years experience
Experienced Data Analytics Trainer with expertise in transforming raw data into actionable business insights. Skilled in data visualization, statistical analysis, business intelligence, and reporting....
Technologies Covered
dbt Core
dbt Cloud
SQL
Python
Jinja
Data Modeling
Data Transformation
dbt Models
dbt Tests
dbt Macros
dbt Snapshots
Git and GitHub
Snowflake
BigQuery
PostgreSQL
Projects
- End-to-End Data Transformation Pipeline Using dbt
- Sales Data Warehouse Modeling
- Customer Analytics Data Model
- Data Quality Testing and Validation
- Incremental Data Processing Project
FAQ
dbt (Data Build Tool) is used to transform, test, document, and manage data models inside data warehouses using SQL and software engineering practices.
Yes. Basic to intermediate SQL knowledge is important because dbt primarily uses SQL to build and manage data transformation models. Basic Python knowledge is also beneficial for advanced concepts.
Learners can explore roles such as dbt Developer, Analytics Engineer, Data Engineer, SQL Developer, and Data Warehouse Developer.