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Data Engineering, Big Data, and ML on GCP

Coursera · Google Cloud · Updated March 2026

Platform rating

4.4/5

AI Tutor Rating

8.2/10

Duration

3-6 months

Classes

150

Master data engineering on Google Cloud including Spark, Kafka, data pipelines, data warehousing, and machine learning deployment.

What you'll get

Build scalable ETL/ELT data pipelines

Process big data with Apache Spark

Design data warehouses and data lakes on GCP

Course Curriculum

12 chapters

Fit

Best for

Software Engineers

DevOps/MLOps Engineers

Data Engineers

Platform Engineers

Not ideal for

Complete beginners

Non-technical learners

Prerequisites & pricing

Prerequisites

Basic SQL and Python

Pricing

Subscription

Certification

Certificate

Growth Leverage: Completing this course opens pathways to roles such as Data Engineer, Big Data Developer, or Machine Learning Engineer, particularly within organizations utilizing Google Cloud. It also prepares participants for relevant certifications like Google Cloud Professional Data Engineer, enhancing their career prospects in the data engineering field.

Skills Value: The skills learned enable solving complex data integration and analysis challenges using technologies like Apache Spark and Kafka, which are in high demand; data engineering roles typically command salaries averaging $100,000 to $130,000 annually, reflecting significant market value.

Data Engineering

BigQuery

Spark

Kafka

GCP

Data Pipelines

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