📊 Google Cloud Data Engineer: Transform Data into Insights
A Google Cloud Certified Professional Data Engineer designs and builds data processing systems. This training equips you with the skills to analyze data, build machine learning models, and automate business processes using Google Cloud Platform (GCP).
Program Fast-Facts
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Duration: 25 Hours of high-quality, expert-led training.
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Practice: 12 Assignments and 2 Real-world Projects.
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Reputation: Rated 4.8/5 by learners, focusing on practical real-time application.
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Current Offer: Priced at ₹29,250 (Original: ₹32,500) | Includes a Free additional self-paced course!
🛠️ Deep Dive into the Syllabus
The curriculum is meticulously designed to help you clear the Google Professional Data Engineer exam.
Key Learning Modules:
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Data Infrastructure: Setting up and managing Google Cloud Storage and BigQuery.
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Data Processing: Mastering Dataflow (Apache Beam) and Dataproc (managed Spark/Hadoop).
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NoSQL & Streaming: Working with Bigtable for high-speed data and Pub/Sub for real-time messaging.
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Machine Learning & AI: Introduction to Vertex AI and pre-built ML APIs to automate insights.
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Data Visualization: Using Looker (formerly Data Studio) to generate business-ready reports.
🌟 Why Choose ITGuru for GCP?
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Lifetime Access: Permanent access to the Learning Management System (LMS) for all presentations and guides.
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Real-World Case Studies: Training is centered around actual industry scenarios rather than just theory.
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24/7 Expert Support: A dedicated team is available around the clock to assist with lab setups or technical queries.
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Placement Assistance: ITGuru’s support team works with 200+ global companies to pass your resume to hiring managers post-completion.
📈 Who Can Enroll?
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Aspiring Data Engineers: Anyone with a basic degree looking to enter the cloud data field.
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Data Analysts: Wanting to scale their analytics capabilities to the cloud.
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Database Administrators: Transitioning from on-premise systems to GCP.
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Software Developers: Interested in building data-driven applications.
Pro Tip: Google Cloud Data Engineering is currently one of the highest-paying certifications in the IT industry. Combining this with a free self-paced course in Python or Big Data (included in the offer) can significantly boost your market value.
❓ Frequently Asked Questions
Are there upcoming batches? New batches are scheduled across March and April 2026:
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Weekday: March 10th (8:00 PM IST) or March 20th (10:00 PM IST).
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Weekend: March 14th (8:00 PM IST).
What if I miss a live class? Every session is recorded and uploaded to your LMS portal, ensuring you never fall behind.
Can I pay in installments? Yes, installment options are available to make the certification journey more affordable.
🚀 Start Your Data Journey
Ready to become a Google Certified Professional?
Curriculum
- 8 Sections
- 0 Lessons
- 25 Hours
- Module 1: Introduction to Cloud Data EngineeringThis module introduces data engineering fundamentals, cloud computing concepts, data lifecycle management, data ecosystems, and the role of a Cloud Data Engineer. Students will learn how cloud platforms enable scalable data processing and analytics solutions.0
- Module 2: Data Storage and Database TechnologiesStudents will learn relational databases, NoSQL databases, data lakes, data warehouses, lakehouses, cloud storage services, and data architecture principles. The module focuses on designing efficient and scalable storage solutions for enterprise data workloads.0
- Module 3: Data Integration, ETL, and Data PipelinesThis module covers ETL/ELT processes, data ingestion techniques, data transformation, workflow orchestration, batch processing, and pipeline automation. Students will learn how to build reliable data pipelines that move and process data across multiple systems.0
- Module 4: Big Data Processing and Distributed SystemsStudents will explore Hadoop, Apache Spark, distributed computing, data processing frameworks, batch processing, and large-scale analytics. The module focuses on handling massive datasets efficiently in cloud environments.0
- Module 5: Cloud Platforms and Data Engineering ServicesThis module introduces AWS, Microsoft Azure, and Google Cloud data engineering services including BigQuery, Dataflow, Dataproc, Azure Data Lake, AWS Glue, and cloud-native data processing tools. Students will learn how to build scalable cloud data solutions.0
- Module 6: Data Quality, Security, and GovernanceStudents will learn data validation, data quality frameworks, governance policies, metadata management, data lineage, security controls, compliance standards, and cloud data protection techniques. The module focuses on maintaining trusted and secure data platforms.0
- Module 7: Real-Time Streaming and Advanced AnalyticsThis module covers Apache Kafka, Pub/Sub, Dataflow, streaming analytics, event-driven architectures, real-time data processing, and modern analytics solutions. Students will learn how to process and analyze streaming data for business applications.0
- Module 8: Real-World Projects, Certification, and Career PreparationStudents will work on end-to-end cloud data engineering projects involving data lakes, ETL pipelines, cloud analytics platforms, and real-time processing systems. The module also includes certification preparation, interview questions, resume building, and career guidance for roles such as Cloud Data Engineer, Data Engineer, Big Data Engineer, Analytics Engineer, and Data Platform Engineer.0
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