GCP Data Engineer Course

11 Lesson

30 Hours

Add to Wishlist

Advance your data engineering skills with igmGuru’s Data Engineering on GCP course. This comprehensive program provides in-depth knowledge of designing, building and managing scalable data pipelines using Google Cloud services such as Cloud Storage, BigQuery, Dataflow, Dataproc, Pub/Sub and Cloud Composer. Through hands-on learning and real-world scenarios, you will gain practical experience in batch and streaming data processing, data warehousing, orchestration, security, monitoring and cost optimization on GCP. Designed for professionals aiming to build reliable, production-ready data platforms, this course equips you with the essential skills required to succeed as a Google Cloud data engineer.

Enroll Now

Google Cloud Platform GCP Data Engineer Course

Overview

Prerequisites for Google Cloud and Data Engineering Course

Basic knowledge of cloud computing
Familiarity with programming (Python or Java)
Understanding of data structures and algorithms
Experience with SQL and relational databases
Knowledge of data engineering concepts (ETL, data pipelines)
Basic understanding of networking concepts
Familiarity with Linux/Unix operating systems
Experience with version control (Git)
Understanding of machine learning basics (recommended but not mandatory)

What Will You Learn

Google Cloud Platform core services and architecture
Data engineer roles and responsibilities on GCP
GCP resource hierarchy, regions, and zones
Cloud Storage and data lake design on GCP
Data ingestion techniques and file formats
BigQuery architecture, datasets, and tables
Writing and optimizing SQL queries in BigQuery
BigQuery cost management and optimization
Batch data processing using Dataflow and Dataproc
Apache Beam fundamentals
Real-time data processing with Pub/Sub
Streaming data pipelines with Dataflow
Data orchestration using Cloud Composer (Airflow)
Visual ETL with Cloud Data Fusion
End-to-end data pipeline design on GCP
Operational databases using Cloud SQL and Spanner
Wide-column storage with Cloud Bigtable
Change Data Capture (CDC) patterns
BigQuery ML and SQL-based machine learning
Vertex AI basics for ML workflows
Data security and IAM on Google Cloud
Data governance with Data Catalog and DLP
Monitoring and logging data pipelines
Designing reliable and fault-tolerant data architectures
Cost optimization and best practices for GCP data services

Who Should Do This Training

Aspiring data engineers
Data analysts transitioning to data engineering
Software engineers working with data pipelines
Cloud engineers using Google Cloud Platform
Big data professionals
ETL and data warehouse developers
Analytics engineers
Database administrators
Machine learning engineers working with data pipelines
IT professionals involved in data and cloud projects

Key Features

1 On 1 Training Option Available
24 X 7 Lifetime Support & Access
Small Batches Upto 10 Participants
Experienced & Professional Trainers
100% Job Assistance
Flexible Schedule

Course Curriculum

Lesson 1 - Introduction to Google Cloud and Data Engineering

1. Overview of Google Cloud Platform services

2. Data engineer roles and responsibilities

3. GCP resource hierarchy: organizations, folders, projects

4. Regions, zones and multi-region concepts

Lesson 2 - Storage and Data Lakes on Google Cloud

1. Cloud Storage concepts: buckets, classes, lifecycle management

2. Designing data lakes on GCP

3. File formats: CSV, Parquet, Avro, ORC

4. Data ingestion into Cloud Storage

Lesson 3 - BigQuery – Enterprise Data Warehouse

1. BigQuery architecture and storage

2. Datasets, tables, views, partitions, clustering

3. Standard SQL in BigQuery

4. Designing schemas and optimizing queries

5. BigQuery pricing and cost optimization

Lesson 4 - Batch Data Processing with Dataflow and Dataproc

1. Introduction to Dataflow and Apache Beam

2. Building batch pipelines with Dataflow

3. Using Dataproc for Spark and Hadoop workloads

4. When to choose Dataflow vs Dataproc

Lesson 5 - Real-Time / Streaming Data Processing

1. Pub/Sub fundamentals (topics, subscriptions, message flow)

2. Streaming pipelines with Dataflow and Pub/Sub

3. Windowing, triggers and late data handling

4. Streaming inserts into BigQuery

Lesson 6 - Data Integration and Orchestration

1. Cloud Data Fusion overview (visual ETL)

2. Cloud Composer (Apache Airflow) and workflow orchestration

3. Scheduling jobs with Cloud Scheduler and Workflows

4. Building end-to-end data pipelines

Lesson 7 - Operational Databases and Analytics Integration

1. Cloud SQL (MySQL/Postgres), Cloud Spanner basics

2. Cloud Bigtable for wide-column storage

3. Integrating OLTP sources with BigQuery and Dataflow

4. Change data capture (CDC) patterns

Lesson 8 - Machine Learning with Google Cloud Data

1. BigQuery ML: creating and using ML models in SQL

2. Vertex AI overview for model training, deployment and prediction

3. Feature engineering using Dataflow and BigQuery

4. Integrating ML predictions into data pipelines

Lesson 9 - Data Security, Governance and Compliance

1. IAM roles and permissions for data services

2. VPC Service Controls and private access

3. Data Catalog: metadata management and discovery

4. Data Loss Prevention (DLP) and encryption options

Lesson 10 - Monitoring, Logging and Reliability

1. Cloud Logging and Cloud Monitoring for data pipelines

2. Setting up alerts and SLOs for Dataflow/BigQuery jobs

3. Debugging and performance tuning pipelines

4. Designing reliable, fault-tolerant data architectures

Lesson 11 - Cost Management and Best Practices

1. Cost optimization for BigQuery, Dataflow, Storage

2. Quotas, limits and scaling considerations

3. Designing efficient schemas and pipelines

Talk To Us

We are happy to help you

1-800-7430-173 (US Toll Free)

+91 7240740740 (India)

Drop Us a Query

Fields marked * are mandatory

Name

Phone Number

Comments

Request For Live Demo Class

Course Fees

Online Class Room Program

US $ 799.00

100% Money Back Guarantee

Duration : 30 Hrs
Plus Self Paced

Classes Starting From

Fast Track Batch 04 Jul 2026
Weekday Batch 06 Jul 2026
Weekend Batch 04 Jul 2026

Corporate Training

Customized Training Delivery Model
Flexible Training Schedule Options
Industry Experienced Trainers
24x7 Support

Trusted By Top Companies Worldwide

Want to know Today's Offer

Google Cloud Data Engineering Certification Training

This course aligns with the Google Cloud Professional Data Engineer certification.

Certification Name: Google Cloud Professional Data Engineer

Exam Format

Exam Name: Professional Data Engineer
Mode: Online proctored or onsite test center (Kryterion)
Question Type: 40-50 Multiple-choice and multiple-select
Duration: 2 hours
Passing Score: Not publicly disclosed by Google
Language: English, Japanese
Attempts: Unlimited (14-day waiting period applies after a failed attempt)

Course Credential

Learners also receive an igmGuru Course Completion Certificate, validating practical knowledge in:

Designing data processing systems on Google Cloud
Building batch and streaming data pipelines
Data warehousing with BigQuery
Dataflow and Dataproc implementations
Data security, governance, and monitoring on GCP

Google Cloud Data Engineering Certification Training

Reviews

Login

Email ID*

Password*

Forgot Password?

GCP Data Engineer Course

Overview