Master Google Data Engineering
Master modern data engineering with Google Cloud — build real pipelines using BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Composer.
Next Batch Details
Program Investment
Google Cloud Data Tracks
BigQuery
Data Warehousing
Dataflow
ETL & Streaming
Dataproc
Spark/Hadoop
Pub/Sub
Messaging
…and many more. For the full curriculum, check our course content
Google Cloud Data Engineering Stack
Ingest
- Cloud Storage
- Pub/Sub
- Transfer Service
Process / Transform
- Dataflow (Beam)
- Dataproc (Spark)
- Databricks
- PySpark
- dbt
Store / Warehouse
- BigQuery
- Bigtable
- Cloud Spanner
- Cloud SQL
Orchestrate
- Cloud Composer
- Data Fusion
Visualize / Analytics
- Looker Studio
- Looker
AI & ML (Optional)
- BigQuery ML
- Vertex AI
Why Choose This Program
Become a complete Google Cloud Data Engineer — from data ingestion to orchestration and analytics.
End-to-End Data Pipelines
Design and deploy production-grade data pipelines using BigQuery, Dataflow, Dataproc, and Pub/Sub.
Hands-on Projects
Work on real-world datasets using GCP services and simulate enterprise-level data architectures.
GCP Ecosystem Mastery
Learn key Google Cloud services like BigQuery, Dataflow, Dataproc, and Cloud Composer.
Real-time Analytics
Build streaming data pipelines with Pub/Sub, Dataflow, and BigQuery for live analytics.
Recorded Sessions
Get full access to all class recordings and study material to learn at your own pace.
Certification Ready
Covers all topics aligned with the Google Cloud Professional Data Engineer certification.
Master Google Cloud Data Tools
Learn everything from Python and SQL foundations to advanced orchestration, monitoring, and BI on Google Cloud.
Core Programming & Querying
4 tools covered
Python
Primary language for data engineering, automation, and scripting
SQL
Foundation for querying and transforming data in warehouses
Pandas
Python library for data manipulation and analysis
Jupyter / Colab
Interactive notebooks for experimentation and learning
Data Storage & Management
4 tools covered
Google Cloud Storage (GCS)
Object storage for data lakes
BigQuery
Serverless data warehouse
Bigtable
NoSQL database for analytics
Cloud Spanner
Globally distributed relational database
Data Processing & Analytics
4 tools covered
Cloud Dataproc
Managed Spark & Hadoop clusters
PySpark
Python API for distributed data processing
Databricks on GCP
Unified analytics platform for big data
Cloud Dataflow
Stream & batch processing with Apache Beam
Data Integration & Orchestration
3 tools covered
Cloud Composer
Managed Apache Airflow for pipeline orchestration
Cloud Pub/Sub
Real-time event streaming and messaging
Cloud Data Fusion
Visual data integration service
Data Governance & Monitoring
2 tools covered
Data Catalog
Data discovery and metadata management
Cloud Logging & Monitoring
Observability, metrics, and alerts
Business Intelligence & Visualization
2 tools covered
Looker
Modern BI and semantic modeling platform
Looker Studio
Self-service dashboards and reporting
End-to-End Real-World Data Engineering Projects
Gain hands-on experience with industry-grade projects simulating enterprise data engineering workflows across diverse domains.
Retail E-Commerce Analytics Pipeline
Build a complete analytics pipeline that processes online retail data — from ingestion to visualization — enabling actionable product and customer insights.
- Ingest order & product data from CSV/JSON sources into GCS
- Transform data using PySpark jobs in Dataproc
- Automate daily ETL pipelines using Cloud Composer
- Load curated datasets into BigQuery
- Build Looker dashboards for sales & customer trends
Online Banking – Fraud Detection & Insights
Implement an intelligent fraud detection system using GCP tools to process banking transactions, detect anomalies, and generate real-time risk insights.
- Ingest raw transaction logs into GCS
- Detect anomalies using Spark ML on Dataproc
- Automate fraud checks & daily reports in Cloud Composer
- Store results in BigQuery for dashboards & audits
- Use Data Catalog & Policy Tags for secure data governance
Healthcare – Patient & Hospital Analytics
Develop a secure, compliant analytics platform for hospitals to analyze patient flow, bed utilization, and operational KPIs at scale.
- Ingest patient & hospital datasets into GCS
- Cleanse and join data using Dataproc with PySpark
- Automate weekly reporting pipelines in Cloud Composer
- Analyze KPIs with BigQuery and build dashboards in Looker
- Implement metadata governance with Data Catalog
Certifications & Career Growth
Get certified and land high-paying data engineering roles at top companies
Certification Path
Career Opportunities
Expected Salary Range
Frequently Asked Questions
Everything you need to know about our Google Cloud Data Engineering program
Interested in Next Batch? Let Us Know
Fill out the form and we'll contact you with batch details, schedule, and more.