The gap between theoretical knowledge and real-world data engineering can be vast. This course is designed to bridge that gap, offering a hands-on, end-to-end project that simulates a real banking data platform on Google Cloud. You will build production-style pipelines using Cloud SQL, GCS, Pub/Sub, BigQuery, Dataproc, PySpark, and Airflow, gaining the practical experience to confidently discuss and implement data solutions in a professional setting.

This Course Offers

• A complete, hands-on banking data engineering project: You will build a full project from start to finish, designing a data platform architecture that uses multiple GCP services in a realistic scenario.
• Practical skills in batch and streaming ingestion: You will build batch ingestion pipelines from Cloud SQL to GCS and streaming ingestion pipelines from Pub/Sub to BigQuery, handling real-time banking events.
• Expertise in PySpark and the medallion architecture: You will create Bronze, Silver, and Gold data layers using PySpark on a Dataproc cluster, preparing business-ready tables for analytics.
• Knowledge of workflow orchestration with Apache Airflow: You will orchestrate your pipelines with Airflow DAGs and learn how to connect CI/CD with GitHub and Cloud Build.

Why We Love This Course

1. It is a project-based, portfolio-building experience. You can tell the course is designed to give you a tangible, real-world project to discuss in interviews, which is invaluable for career advancement.
2. It demonstrates the integration of multiple GCP services. The course shows you how Cloud SQL, GCS, Pub/Sub, BigQuery, Dataproc, and Airflow work together, providing a holistic view of a data platform.
3. It is focused on a realistic banking use case. The project uses a banking domain, which is a common and highly relevant use case for data engineering roles.
4. It is designed for aspiring data engineers. The course is perfect for those who have some knowledge of SQL and Python and want to take the next step by building a complete, professional project.

Building a real-world data engineering project is the most effective way to solidify your skills and impress employers. This course provides a clear, practical, and comprehensive path to building that expertise. It is backed by a money-back guarantee if it does not meet your expectations.

• This course is perfect for aspiring data engineers who want hands-on project experience with Google Cloud Platform.
• It is ideal for learners preparing for data engineering interviews who need a practical banking project to explain confidently.
• The course is also great for students, cloud engineers, data analysts, and ETL developers who want to transition into GCP data engineering roles.

• A basic understanding of SQL and Python is helpful.
• Basic familiarity with Google Cloud Platform is useful, but the required setup is explained in the course.
• Learners should have a Google Cloud account to practice the project hands-on.

Interested in exploring more lessons? Check out our full course library to continue building your skills and advancing your learning journey.