Google Cloud Professional Data Engineer

Name: Google Cloud Professional Data Engineer
Availability: InStock

Prepare for the Google Cloud Professional Data Engineer certification with hands-on coverage of BigQuery, Dataflow, Pub/Sub, Bigtable, Spanner, Vertex AI, and Cloud Composer. Build production-grade data pipelines, architect storage solutions for scale, and master data governance using Dataplex — all aligned to the official GCP PDE exam domains.

4.80/5.0

13 hours

2 enrolled

Updated May 2026

Course Content ↓

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By James Chen

What You'll Learn

Explain BigQuery's Dremel-based distributed query architecture and columnar storage model

Identify the correct GCP storage service for OLTP, analytics, time-series, and globally consistent workloads

Build streaming and batch data pipelines using Apache Beam on Cloud Dataflow with Pub/Sub as the message layer

Apply BigQuery ML to train, evaluate, and deploy machine learning models using SQL

Automate data workflows using Cloud Composer DAGs and implement idempotent, retry-safe pipeline patterns

Evaluate data quality, lineage, and governance policies using Dataplex Universal Catalog across distributed data assets

Prerequisites

Hands-on experience with at least one cloud platform (AWS, Azure, or GCP basics)
SQL proficiency including window functions and aggregate queries
Familiarity with Python for scripting data pipelines
Basic understanding of distributed systems concepts (partitioning, replication, consistency)
Google Cloud Associate Cloud Engineer certification or equivalent practical experience

About the Instructor

James Chen

Expert instructor with hands-on industry experience in Cloud.

Included in paid plans

LevelAdvanced

Duration13 hours

Lessons—

Students2

Rating4.80 / 5.0

Cert targetGCP PDE

This course includes

Hands-on practice labs
AI-powered explanations
Progress tracking
Certificate of completion
Lifetime access

30-day money-back guarantee