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Instructor-led training
Professional Data Engineer Training in London and Live Online

Google Cloud Professional Data Engineer

Design and operate reliable data systems on Google Cloud. Explore ingestion, storage, batch and streaming pipelines, analytics, governance and operational optimisation.

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Price:
Price on request

Contact us for current fees, dates and exam arrangements.

Advanced

Be comfortable with SQL and a programming language such as Python.

5 days to complete
Available online
& in class

Select your preferred method

Course overview
Course dates
  • In Classroom
  • Live Virtual
  • 1 - 1 Training
  • Corporate Training
  • Onsite Training
Introduction
This Professional Data Engineer course develops practical skills for collecting, transforming, storing and serving data on Google Cloud. It is designed for data engineers and technical professionals who work with pipelines, databases and analytical workloads.


Explore data architecture, ingestion patterns and service selection across batch and streaming requirements. Consider security, quality, governance, reliability and cost throughout the data lifecycle. Work through operational scenarios involving orchestration, monitoring and troubleshooting, and prepare data for analytics and machine learning use cases.
The course supports preparation for Google Cloud Professional Data Engineer certification. Certification requires passing Google’s separately administered exam. Review the current exam guide and confirm training dates, practical arrangements and exam fees with London IT Training.
What the course covers
Flexible Ways to Learn

Study your way with flexible learning options designed to fit around your schedule.

Small Groups

With small groups of students, our instructors can work closely with each student

Flexible Class Schedules

Our class schedules are flexible on weekdays, weekend or evening to suit your schedule.

Experienced Instructors

Our instructors follow a modified and personalised approach to engage students during class

Hi-Tech lab Facilities

Lab arrangements vary by course. Confirm access and equipment requirements before booking.

Prerequisites
What you’ll gain

Design data systems aligned with business and operational requirements.

Select ingestion, storage and processing approaches for data workloads.

Apply data quality, security and governance practices.

Monitor, troubleshoot and optimise reliable data pipelines.

Develop skills for your next step
Relevant career pathways
Data Engineer:

Build and operate data ingestion and processing pipelines.

Analytics Engineer: Prepare dependable data models and datasets for analysis.

Cloud Data Engineer:

Implement secure and reliable data systems on Google Cloud.

Syllabus

Data system architecture
Analyse data sources, consumers and workload requirements. Select architectures based on scale, latency, reliability, security and cost.

Compare batch and streaming ingestion patterns. Explore connectors, Pub/Sub and change-driven workflows. Consider schema evolution, validation and handling failed records.

Choose storage and database approaches for analytical workloads. Explore Cloud Storage and BigQuery, data layout, partitioning, modelling and lifecycle management.

Design batch and streaming transformations with suitable managed services. Consider Dataflow and distributed processing patterns, windowing, retries and correctness.

Plan pipeline dependencies, schedules and repeatable deployments. Explore orchestration, environment configuration and safe updates to data workflows.

Apply least privilege, data access controls and encryption. Plan metadata, lineage, data quality checks and retention according to organisational requirements.

Monitor pipeline health, latency and data freshness. Investigate failures and optimise processing, storage and query costs while preserving reliability.

Prepare trustworthy data for analytics and machine learning use cases. Review architecture scenarios and map further practical study to the current certification guide.

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FAQs

Who should attend?
Data engineers and technical professionals working with databases, pipelines and analytical systems.

SQL, a language such as Python, and an understanding of data processing and database concepts.

Google Cloud Professional Data Engineer. Check the current official exam guide for assessed topics.

Its main focus is data engineering: ingestion, storage, processing and reliable operations. It also covers preparing data for analytical and machine learning use cases.

No. Google awards certification after you meet its requirements and pass the separately administered exam.

Contact London IT Training to confirm the quotation and exam arrangements.

Online and classroom options are available. Confirm the schedule and venue with the team.

No. Results depend on preparation, practical experience and other factors.

Need help choosing the right course?

Talk to one of our advisers about dates, delivery options and certification routes. We’ll call you back within 1 working day.

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