Introduction to Data Engineering on Google Cloud Training Course in Germany

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.

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

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.

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 Germany through Bilginç IT Academy's live and interactive virtual classroom environment, accessible from your home, office, or any location. Connect with expert trainers in real time and bring the energy of classroom learning into the digital experience.

Live Instructor-Led Sessions: Join scheduled training sessions with your instructor and fellow delegates in real time.
Interactive Learning Experience: Take part in discussions, practical exercises, group activities, and Q&A sessions throughout the course.
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 long-standing experience in delivering professional training since 1995.
Flexible and Scalable Delivery: Access live virtual classrooms from Germany and worldwide, with flexible planning options for individual and corporate training needs.

Experience Introduction to Data Engineering on Google Cloud in a focused classroom environment in Germany. Bilginç IT Academy's carefully selected training venues provide a professional setting where delegates can interact directly with expert trainers and peers.

Experienced Trainers: Learn from specialists with extensive field experience and real-world knowledge.
Professional Training Venues: Attend courses in comfortable, well-equipped classrooms designed to support effective learning.
Focused Classroom Experience: Benefit from limited class sizes that encourage discussion, interaction, and personalized support.
Quality-Driven Learning: Develop practical skills through structured, up-to-date, and professionally designed training content.

Meet your team's training needs with Bilginç IT Academy's onsite Introduction to Data Engineering on Google Cloud in Germany solution, delivered at your office or preferred location. Align your team's development with your business goals through a training experience tailored to your organization.

Tailored Course Content: Adapt the training program to your organization's projects, team structure, and specific business requirements.
Time and Cost Efficiency: Reduce travel, accommodation, and operational costs while maximizing the value of your training investment.
Team-Focused Learning: Help your employees develop around the same knowledge base and strengthen collaboration across your organization.
Simplified Planning and Tracking: Manage the training process, participant development, and organizational requirements with greater control.

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 Germany (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 Germany. We can customize the curriculum to meet your team's specific needs and organize the session at your preferred location and date within Germany.

Yes, we prioritize location flexibility. We offer live-streaming (hybrid) support for most of our trainings, synchronized with the Germany 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 Germany.

Introduction to Data Engineering on Google Cloud Training in Germany

Prerequisites

What You Will Learn

Training Outline

Why Choose Us

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