Data Engineering on Google Cloud Platform Training

According to Google Cloud, data-driven companies are 23 times more likely to acquire customers and 19 times more likely to be profitable. But building the right infrastructure for data success requires the right skills—and the right cloud platform.

Data Engineering on Google Cloud Platform provides hands-on training in building scalable data pipelines, managing batch and streaming data, and applying machine learning to large datasets. Through immersive hands-on labs, you’ll work directly with Google Cloud Platform (GCP) tools like BigQuery, Cloud Dataflow, Cloud Composer, and Kubeflow to design solutions that drive business intelligence, improve agility, and support real-time decision-making.

This training helps professionals grow their cloud skills and prepare for the Professional Data Engineer certification. It’s ideal for anyone pursuing the role of a data engineer, especially those working with cloud data, big data, or real-time data processing needs.

• Design and implement scalable data pipelines on Google Cloud
• Analyze massive datasets using BigQuery, SQL, and machine learning
• Build both batch data and streaming pipelines with Dataflow and Pub/Sub
• Use Dataproc and Spark to manage big data workloads efficiently
• Automate and deploy AI workflows using BigQuery ML, AutoML, and Kubeflow

• Basic proficiency with a common query language such as SQL.
• Experience with data modeling and ETL (extract, transform, load) activities.
• Experience with developing applications using a common programming language such as Python.
• Familiarity with machine learning and/or statistics.