This course is designed to equip you with essential skills in data engineering on Google Cloud Platform (GCP). Through hands-on labs and real-world scenarios, you’ll learn how to design, implement, and automate data pipelines that are efficient, scalable, and reliable. We’ll cover core GCP services for data engineering, including Cloud Pub/Sub for streaming data ingestion, Cloud Dataflow for data transformation, BigQuery for advanced analytics, and Cloud Composer for orchestration and workflow automation.You’ll start by mastering data ingestion techniques for both batch and streaming data, then move on to data transformation and storage optimization using GCP’s best practices. Additionally, you’ll learn how to monitor and automate your data workflows, ensuring data quality, integrity, and operational efficiency. By the end of the course, you’ll be able to design end-to-end data pipelines tailored to specific business needs, prepare data for analytics and machine learning, and manage these processes with minimal maintenance.This course is ideal for data professionals, cloud engineers, and IT specialists looking to deepen their expertise in data engineering and automation on Google Cloud. Whether you're preparing for the Google Professional Data Engineer Certification or aiming to build advanced data engineering skills, this course provides the practical experience needed to succeed.
What you'll learn
design and implement data pipelines
automate data workflows
utilize GCP services such as BigQuery and Cloud Dataflow
ensure data quality and operational efficiency
Course objectives
master data ingestion techniques
learn data transformation and storage optimization