The Google Cloud Professional Data Engineer Training by Techpratham will help you become an expert at designing, building, and running data processing systems on GCP. You will learn how to use BigQuery, Dataflow, Pub/Sub, Cloud Storage, and machine learning to solve real-world data problems. This training focuses on making sure that data is reliable, scalable, secure, and follows the rules in business settings. It fully prepares you for the Google Cloud Professional Data Engineer certification exam and high-demand cloud data engineering jobs with hands-on labs and projects.
Google Cloud
Google Cloud-Professional Data Engineer
With the Google Cloud Professional Data Engineer Training by Techpratham, you can learn how to process, store, and use machine learning solutions on GCP. This course will help you pass the Professional Data Engineer certification exam and make cloud apps that can grow and are based on data.
5/5(4,890 Reviews)
Level
Advanced
Duration
8 Weeks
Placement Client
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About Google Cloud-Professional Data Engineer
Training Plan
01
About trainer
Working professional who is carrying more then 10 years of industry experience.
02
Decks & Updated Content
Access to updated presentation decks shared during live training sessions.
03
e-Book
E-book provided by TechPratham. All rights reserved.
04
Assignments & MCQs
Module-wise assignments and MCQs provided for practice.
05
Video Recording
Daily Session would be recorded and shared to the candidate.
06
Projects
Live projects will be provided for hands-on practice.
07
Resume Building
Expert-guided resume building with industry-focused content support.
08
Interview Preparation
Comprehensive interview preparation with real-time scenario practice.
<h1><strong>Google Cloud-Professional Data Engineer</strong></h1> Course Curriculum
Introduction to Data Engineering & GCP
Introduction to Data Engineering & GCP covers building, processing, and managing data pipelines using Google Cloud Platform services for scalable analytics.
Role of a Data Engineer
Data engineering lifecycle
Introduction to Hadoop
OLTP vs OLAP
Structured, semi-structured, unstructured data
Batch vs streaming processing
Data pipeline architectures
ETL vs ELT patterns
Linux Commands
Data Engineering Concepts
Data Engineering Concepts cover data ingestion, transformation, storage, and pipeline orchestration to enable reliable and scalable analytics systems.
Overview of Google Cloud Platform
GCP resource hierarchy (Org, Folder, Project)
IAM fundamentals
GCP Console & Cloud Shell
Cloud Storage & Data Lake Design
Cloud Storage & Data Lake Design focus on organizing, storing, and managing large volumes of structured and unstructured data for scalable analytics.
Cloud Storage overview
Buckets, objects, storage classes (Practical)
Lifecycle management
Data lake architecture
File formats (CSV, JSON, Avro, Parquet, ORC)
BigQuery – Data Warehouse
BigQuery is Google Cloud’s fully managed data warehouse that enables fast SQL-based analytics on large-scale datasets.
BigQuery architecture
Datasets, tables, views, Materialized views (Practical)
Standard SQL (Practical)
Loading data into BigQuery (Practical)
Partitioning & clustering (Practical)
Query optimization and cost control (Practical)
Data Ingestion Methods
Data Ingestion Methods involve collecting data from multiple sources using batch, streaming, or real-time pipelines for processing and analytics.
Batch ingestion strategies (Full/Delta)
Streaming ingestion strategies
Data transfer from on-prem & cloud
External data sources integration
Data Integration & ETL
Data Integration & ETL involve extracting data from sources, transforming it into usable formats, and loading it into target systems for analysis.
Cloud Data Fusion overview
Google Cloud Courses
No related courses found
Additional Program Highlights
Comprehensive study materials and resources
HD
Professional resume building session
HD
Master your interview skills
HD
Real-world project demonstrations
HD
Upcoming Batches
Can't find a batch you were looking for?
Who Should Take <h1><strong>Google Cloud-Professional Data Engineer</strong></h1>
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Working Professionals
Ops/Administrators/HR
Developers
BA/QA Engineers
Cloud / Infra
IT Professionals
Non-IT Career Switchers
Fresh Graduates
Key Projects
<h1><strong>Google Cloud-Professional Data Engineer</strong></h1>
Real-Time Data Pipeline with Pub/Sub and Dataflow
You will use Cloud Pub/Sub and Dataflow to build a pipeline that takes in and processes data in real time for this project. BigQuery will collect, change, and store streaming data so that it can be analyzed. This project focuses on scalability, fault tolerance, and an architecture based on events.
Big Data Analytics with BigQuery and Looker Studio
This project is all about using BigQuery to look at big datasets and Looker Studio to make interactive dashboards. You will use advanced SQL, optimize queries, and work with partitioned and clustered tables. The final dashboard will give you business intelligence insights and let you report on them in real time.
Machine Learning Integration with Vertex AI & BigQuery ML
You will use BigQuery ML and Vertex AI to train and deploy a machine learning model in this project. This will help you make predictions. You will put the model into a data pipeline so that it can make predictions automatically. This will show how AI can be used to make decisions in the cloud.
Placement Process
Live Class with Industry Use Cases
- Interactive learning
- Real-world examples
- Expert guidance
- Doubt resolution
Daily Assignment & Weekly Assessments
- Hands-on practice
- Concept reinforcement
- Weekly evaluation
- Timely feedback
Project Testing & Deployment
- Project development
- Testing practice
- Deployment exposure
- Portfolio creation
Interview Preparation (Mock, PD, Alumni Session)
- Mock interviews
- Personal development
- Alumni guidance
- Confidence building
Resume Building
- Resume crafting
- Industry-focused format
- Skills highlighting
- Professional presentation
Placement
- Job assistance
- Interview support
- Career guidance
- Opportunity access
Latest Hiring
No hiring posts
Recently Placed Candidates
No placements available
Latest Hiring
No hiring posts
Our Success Mantra
Commitment
- Ensuring quality training every day
Fulfillment
- Meeting learning goals with confidence
Accomplishment
- Students achieving industry-ready expertise
Our Learner Voice
Beyond Courses:
Additional Support We Provide
24/7 Support
LinkedIn Profile
Resume Writing
Alumni Sessions
Interview Preparation
Live Projects
What Makes TechPratham Training Different?
Feature
TechPratham Advantage
Industry Standard Institutes
Real-World Implementation
Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.
Restricted or simulation-based access that lacks real-world complexity.
Subject Matter Experts
Mentorship from certified professionals with 15+ years of global industry experience.
Generic instructors with no hands-on implementation background.
2026 Ready Curriculum
AI-driven curriculum with advanced platform integrations and real-world configurations.
Basic, outdated syllabus that misses key technical integrations.
Daily & Weekly assignments
Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.
Self-paced learning with no accountability or progress tracking.
End-to-End Lifecycle
Hands-on project testing and deployment with portfolio-ready real-world exposure.
Basic lab exercises without any deployment or testing practice.
Interview Readiness
Structured interview preparation including mock interviews, PD sessions, and alumni guidance.
Minimal support limited to a generic certificate of completion.
Placement Support
Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.
Basic career tips with no direct industry connections.
Training Support
24/7 technical doubt resolution and personalized mentoring support.
Limited mentor availability and no support after class hours.
Affordable Fees
Competitive fixed pricing with flexible payment options and transparent fee structure.
Inflated fees with hidden costs and low return on investment.
Real-World Implementation
Live enterprise tenant access for 24/7 practice on real-world, enterprise-grade scenarios.
Restricted or simulation-based access that lacks real-world complexity.
Subject Matter Experts
Mentorship from certified professionals with 15+ years of global industry experience.
Generic instructors with no hands-on implementation background.
2026 Ready Curriculum
AI-driven curriculum with advanced platform integrations and real-world configurations.
Basic, outdated syllabus that misses key technical integrations.
Daily & Weekly assignments
Daily assignments and weekly assessments focused on concept reinforcement and continuous feedback.
Self-paced learning with no accountability or progress tracking.
End-to-End Lifecycle
Hands-on project testing and deployment with portfolio-ready real-world exposure.
Basic lab exercises without any deployment or testing practice.
Interview Readiness
Structured interview preparation including mock interviews, PD sessions, and alumni guidance.
Minimal support limited to a generic certificate of completion.
Placement Support
Guaranteed interview support through tie-ups with top MNCs and 1-on-1 mock interview sessions.
Basic career tips with no direct industry connections.
Training Support
24/7 technical doubt resolution and personalized mentoring support.
Limited mentor availability and no support after class hours.
Affordable Fees
Competitive fixed pricing with flexible payment options and transparent fee structure.
Inflated fees with hidden costs and low return on investment.
What is Google Cloud Professional Data Engineer Training?
Who can take the Data Engineer certification course from Tech Pratham?
What tools are covered in the Google Cloud Data Engineer course?
What is Cloud Composer, and why is it used?
What is the format of the Professional Data Engineer exam questions?
What are some common challenges Data Engineers face?
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