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 end-to-end data pipelines
implement data ingestion techniques for batch and streaming data
transform and optimize data storage using GCP best practices
monitor and automate data workflows
Course objectives
equip students with essential data engineering skills
prepare students for the Google Professional Data Engineer Certification
enable students to ensure data quality and operational efficiency