The Complete Databricks Project on Google Cloud (GCP)

Are you looking to master Databricks on Google Cloud (GCP) with a real-world, end-to-end project? This course is designed to give you hands-on experience with one of the most in-demand skills in data engineering: building scalable data pipelines using Databricks, PySpark, and Medallion Architecture.

In this project, we take on the role of a government transport agency analyzing road traffic data. You will learn how to manage road infrastructure datasets, process traffic counts from sensors, and generate insights such as the busiest regions, EV adoption trends, and year-over-year traffic volume.

We will start by setting up Databricks on GCP, creating buckets, external locations, and Unity Catalog, and then move step by step through Bronze, Silver, and Gold layers using Auto Loader and Structured Streaming. You’ll gain real-world exposure to data ingestion, transformation, and aggregation pipelines.

The course also goes beyond development by covering workflow orchestration, GitHub integration, and CI/CD practices. You will learn how to set up Dev, UAT, and Production environments, manage code using Git branches, and promote pipelines using pull requests – just like in real industry projects.

By the end of this course, you will not only have built a portfolio-ready project, but also be equipped with the practical knowledge and interview-ready concepts to crack Data Engineering roles involving Databricks and GCP.

Whether you’re a beginner or a working professional, this project-based course ensures you learn by doing – and walk away with confidence in both technical skills and real-world applications.