Google Cloud Data Engineer


On this Google Cloud Data Engineer Skills Bootcamp, you'll attain the fundamentals of cloud-based data solutions with an emphasis on Google Cloud Platform. You'll learn to harness the Google Data platform to design data processing systems, ensure quality, machine learning and operationalize data processing systems.

Businesses benefit from delegates taking a data-driven decision-making approach - utilising data to inform stakeholders and colleagues. Businesses that used Google Cloud can benefit of delegates having specific knowledge of related to this and a fundamental knowledge of other platforms too.

This pathway is aimed at Level 5 delegates and is 11 weeks.

Firebrand deliver the programme through Online Instructor-Led learning, based on our Lecture | Lab | Review methodology. Apprentices will be supplemented with support from our Data Subject Matter Experts (SMEs), and get full access to an e-learning platform.

Firebrand take sole delivery of the Google Cloud Data Engineer Skills Bootcamp provision and will provide the operational infrastructure to recruit learners, deliver training, provide additional support to learners and to access a guaranteed interview with employers who are regularly hiring people with these skills.


Course AZ-900T01-A: Microsoft Azure Fundamentals

  • Module 1: Cloud concepts
  • Module 2: Azure architecture and services
  • Module 3: Azure management and governance

Google Cloud Certified - Professional Data Engineer

Part A:

  • Module 1: Introducing Google Cloud Platform
  • Module 2: Compute and Storage Fundamentals
  • Module 3: Data Analytics on the Cloud
  • Module 4: Scaling Data Analysis
  • Module 5: Machine Learning
  • Module 6: Data Processing Architectures
  • Module 7: Summary

Part B:

  • Module 1: Google Cloud Dataproc Overview
  • Module 2: Running Dataproc Jobs
  • Module 3: Integrating Dataproc with Google Cloud Platform
  • Module 4: Making Sense of Unstructured Data with Google's Machine Learning APIs
  • Module 5: Serverless data analysis with BigQuery
  • Module 6: Serverless, autoscaling data pipelines with Dataflow
  • Module 7: Getting started with Machine Learning
  • Module 8: Building ML models with Tensorflow
  • Module 9: Scaling ML models with CloudML
  • Module 10: Feature Engineering
  • Module 11: Architecture of streaming analytics pipeline
  • Module 12: Ingesting Variable Volumes
  • Module 13: Implementing streaming pipelines
  • Module 14: Streaming analytics and dashboards
  • Module 15: High throughput and low-latency with Bigtable

Part C:

  • Module 1: Understanding the Professional Data Engineer Certification
  • Module 2: Sample case studies for Professional Data Engineer exam
  • Module 3: Designing and Building Review
  • Module 4: Analysing and Modelling Review
  • Module 5: Reliability, Policy and Security Review

Exam Track

As part of this Skills Bootcamp, you'll sit the following exams:

Exam AZ-900: Microsoft Azure Fundamentals

  • Exam code: AZ-900
  • Language: English
  • Domains:
    1. Describe cloud concepts (20-25%)
    2. Describe core Azure services (15-20%)
    3. Describe core solutions and management tools on Azure (10-15%)
    4. Describe general security and network security features (10-15%)
    5. Describe identity, governance, privacy, and compliance features (20-25%)
    6. Describe Azure cost management and Service Level Agreements (10-15%)

Google Cloud Certified Professional Data Engineer exam

  • Format: Multiple choice/multiple select
  • Duration: 2 hours
  • Languages: English, Japanese, Spanish and Portuguese
  • Domains:
    1. Design data processing systems
    2. Build and operationalising data processing systems
    3. Operationalising machine learning methods
    4. Ensure solution quality

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