Cloud Data Engineering Career Accelerator (Google Professional Data Engineer Track)
Build Scalable Data Systems — The Backbone of Modern AI & Analytics
Design. Build. Scale. Become a High-Value Data Engineer.
Level: Advanced
Prerequisite: Python + SQL + Data Analytics / ML basics
Duration: 14–18 weeks (Cohort-Based)
Format: Live + Hands-On Labs + System Design Projects
Powered by: Google Cloud
Certification: Google Professional Data Engineer
Start Date: [Insert Next Cohort Date]
Seats: Limited to 15 learners
Go beyond analytics and machine learning. Learn how to design, build, and manage data pipelines and systems that power real-world applications at scale.
By the end of this program, you will:
Design and build data pipelines (ETL/ELT)
Work with data warehouses (BigQuery)
Process large-scale datasets in cloud environments
Implement data engineering best practices
Deploy and manage data systems for analytics and AI
Google Cloud Platform (BigQuery, Data tools)
Python
SQL
Data pipeline frameworks
Cloud architecture tools
End-to-end data pipelines
Cloud-based data warehouse solutions
Scalable analytics systems
Portfolio-ready engineering project
Weeks 1–3: Data Engineering Foundations
Data architecture principles
Cloud data systems overview
Designing scalable solutions
Weeks 4–7: Data Pipelines & Warehousing
ETL/ELT workflows
BigQuery and cloud storage
Data ingestion & transformation
Weeks 8–11: Data Processing at Scale
Batch and streaming data processing
Performance optimization
Monitoring and reliability
Weeks 12–14: Data for Machine Learning
Preparing data for ML pipelines
Feature engineering workflows
Integration with AI systems
Weeks 15–18: Capstone Project
Design and build a full data pipeline
Deploy a cloud-based data system
Present architecture and outcomes
This program prepares you for:
Data Engineer
Cloud Data Engineer
Analytics Engineer
AI/Data Infrastructure Specialist
Premium Cloud Program
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Leverage skills to unlock opportunities—employment, enterprise growth, and partnerships.
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