This course is a comprehensive, hands-on course designed to help you master the design, implementation, and optimization of batch data pipelines in the Google Cloud ecosystem. With organizations generating massive volumes of data, the ability to build efficient, reliable, and scalable batch pipelines is essential for modern data engineering and analytics. This course introduces the core concepts of data pipelines, explores common patterns such as EL, ELT, and ETL, and teaches you how to select the right approach based on workload requirements, data volume, transformation complexity, and performance needs.

You’ll work directly with Google Cloud’s powerful tools—including BigQuery, Dataproc, Dataflow, Cloud Data Fusion, and Cloud Composer—to build production-ready batch processing solutions. Through guided labs and real-world scenarios, you’ll gain practical experience running Spark on Dataproc, orchestrating end-to-end workflows, leveraging serverless processing with Dataflow, and managing pipelines with Cloud Data Fusion and Cloud Composer.