The Complete GCP Data Engineering Project - Retailer Domain
Step-by-Step GCP Data Engineering with BigQuery & Airflow
Created by Shaik Saidhul
Explore the process of building a complete data engineering pipeline on Google Cloud Platform. Gain hands-on experience with BigQuery, PySpark, and Airflow as you work through real-world retailer data workflows. Develop practical skills for designing, automating, and deploying scalable cloud-based solutions.
Packt | May 2026 | 370 min
What You Will Learn
You will build a practical data project step by step, combining theory with hands-on activities. Each section guides you through ingesting, transforming, and orchestrating data using GCP tools. By applying what you learn in real scenarios, you will develop the confidence to manage end-to-end data workflows on the cloud.
Key Features
- Design and implement layered data pipelines using BigQuery, PySpark, and Dataproc
- Automate workflow orchestration with Airflow and integrate CI/CD for deployment
- Transform raw data into structured datasets ready for business analysis and insights
Target Audience
Ideal for data engineers and cloud professionals with basic SQL, Python, and cloud knowledge. If you want to strengthen your skills in building, automating, and deploying data pipelines on GCP, this course will help you achieve that goal. It is especially useful for those working with real-world datasets in business or analytics roles.
