Introduction to Data Engineering on Google Cloud Training Course in New Zealand

In this course, you learn about data engineering on Google Cloud, the roles and responsibilities of data engineers, and how those map to offerings provided by Google Cloud. You also learn about ways to address data engineering challenges.

Prerequisites

Before starting this learning path, you should already have:

Prior Google Cloud experience at the fundamental level using Cloud Shell and accessing products from the Google Cloud console.
Basic proficiency with a common query language such as SQL.
Experience with data modelling and ETL (extract, transform, load) activities.
Experience developing applications using a common programming language such as Python.

Target audience

The target audience is aimed at: Data engineers, Database administrators and System administrators.

We can organize this training at your preferred date and location.

What You Will Learn

By the end of this course, learners will:

Understand the role of a data engineer.
Identify data engineering tasks and core components used on Google Cloud.
Understand how to create and deploy data pipelines of varying patterns on Google Cloud.
Identify and utilize various automation techniques on Google Cloud.

Training Outline

Data Engineering Tasks and Components

Explain the role of a data engineer.
Understand the differences between a data source and a data sink.
Explain the different types of data formats.
Explain the storage solution options on Google Cloud.
Learn about the metadata management options on Google Cloud.
Understand how to share datasets with ease using Analytics Hub.
Understand how to load data into BigQuery using the Google Cloud console or the gcloud CLI.

Data Replication and Migration

Explain the baseline Google Cloud data replication and migration architecture.
Understand the options and use cases for the gcloud command-line tool.
Explain the functionality and use cases for Storage Transfer Service.
Explain the functionality and use cases for Transfer Appliance.
Understand the features and deployment of Datastream.

The Extract and Load Data Pipeline Pattern

Explain the baseline extract and load architecture diagram.
Understand the options of the bq command-line tool.
Explain the functionality and use cases for BigQuery Data Transfer Service.
Explain the functionality and use cases for BigLake as a non-extract-load Pattern.

The Extract, Load, and Transform Data Pipeline Pattern

Explain the baseline extract, load, and transform architecture diagram.
Understand a common ELT pipeline on Google Cloud.
Learn about BigQuery’s SQL scripting and scheduling capabilities.
Explain the functionality and use cases for Dataform.

The Extract, Transform and Load Data Pipeline Pattern

Explain the baseline extract, transform, and load architecture diagram.
Learn about the GUI tools on Google Cloud used for ETL data pipelines.
Explain batch data processing using Dataproc.
Learn how to use Dataproc Serverless for Spark for ETL.
Explain streaming data processing options.
Explain the role Bigtable plays in data pipelines.

Automation Techniques

Explain the automation patterns and options available for pipelines.
Learn about Cloud Scheduler and Workflows.
Learn about Cloud Composer.
Learn about Cloud Run functions.
Explain the functionality and automation use cases for Eventarc.

Exams and Assessments

No formal examinations for this course.

Hands-on Learning

Within this course there are opportunities for learners to engage in hands-on labs to support module learning.

In addition, each module will also have a quiz, to support knowledge capture.

Why Choose Us

Experience Introduction to Data Engineering on Google Cloud in New Zealand through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

Delivery Method: Online Instructor-Led
Participation Model: Public / Private (In-house)
Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
Worldwide Access: Join our live virtual classrooms from New Zealand or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience Introduction to Data Engineering on Google Cloud through face-to-face Classroom Based training in New Zealand. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

Delivery Method: Classroom Based
Participation Model: Public / Private (In-house)
Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange Introduction to Data Engineering on Google Cloud in New Zealand as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

Delivery Method: Onsite
Participation Model: Private (In-house)
Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
Worldwide Onsite Delivery: Arrange the training in New Zealand or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.

Why have you chosen us?

I have attended a training from Bilginc IT Academy before and I was satisfied.

I have attended a training from a different provider and it was not helpful.

Other

How many employees do you have in your IT department?

0 – 50

50 – 250

250 – 1000

1000+

Frequently asked questions about Introduction to Data Engineering on Google Cloud Training Course in New Zealand (FAQ)

This training provides a strong introduction to data engineering, but becoming an advanced data engineer typically requires additional practice in SQL, Python, data modeling, ETL/ELT processes, and distributed data processing. It is the right starting point.

This training is valuable for roles such as Data Engineer, Data Analyst, Cloud Data Specialist, BI Developer, and professionals working on data projects with Google Cloud. It is especially useful for those moving into cloud-based data architectures.

This training is suitable for individuals who want to start a career in data engineering, data analysts, software developers, system specialists, and professionals who want to learn data processing on Google Cloud. It provides a strong starting point for understanding data pipelines, storage, and cloud-based data architectures.

Basic data concepts, SQL knowledge, and general awareness of cloud computing are helpful. Advanced programming skills are not mandatory, but familiarity with data processing, databases, and analytics workflows will make the training more effective.

The training covers BigQuery, Cloud Storage, Dataflow, Pub/Sub, and key Google Cloud services related to data processing. Participants learn how data is collected, moved, stored, processed, and prepared for analytics.

Yes, the training clarifies the difference between data engineering and data analytics roles. Data engineering focuses on preparing reliable, scalable, and analysis-ready data, while data analytics focuses on generating insights from that data.

Participants gain the ability to understand cloud data pipelines, manage data processing workflows, and support reliable data infrastructures needed by analytics teams. These skills are valuable in modern data projects.

Yes, the training includes hands-on examples such as working with datasets on Google Cloud, understanding data flows, querying data, and practicing data processing scenarios based on real-world use cases.

Absolutely. We do not only host trainings at public centers; we can also conduct them directly at your premises across New Zealand. We can customize the curriculum to meet your team's specific needs and organize the session at your preferred location and date within New Zealand.

Yes, we prioritize location flexibility. We offer live-streaming (hybrid) support for most of our trainings, synchronized with the New Zealand time zone. If you are unable to visit our location, you can join our physical classroom setting interactively via our digital platforms and participate in hands-on workshops remotely from anywhere in New Zealand.

Introduction to Data Engineering on Google Cloud Training in New Zealand

Prerequisites

What You Will Learn

Training Outline

Why Choose Us

Frequently asked questions about Introduction to Data Engineering on Google Cloud Training Course in New Zealand (FAQ)