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  • TRAINING

Data Engineering - Focus Azure.

Build scalable data platforms, reliable pipelines, and cloud-native infrastructure for analytics and AI. You'll work with Azure, Spark, Snowflake, and dbt to deliver a complete end-to-end project.

Full/Part time
8 weeks (full-time)
German
Data engineer works with big data, cloud technologies and AI analyses.

What is data engineering?

Data engineering is the discipline of building data platforms, pipelines, and cloud-native infrastructure for analytics and AI. In this career track, you'll build modern data warehouses, data lakes, and lakehouses on Azure and implement scalable ETL and ELT pipelines.

Who is this training program suitable for?

This training program is designed for data professionals and developers who want to go beyond analytics. A solid working knowledge of Python, SQL, Git, and Bash is required. You are ready for a 175-hour advanced-level program.

For which professional groups is the training relevant?

This training program prepares you for highly sought-after engineering roles in the fields of cloud and data. It is particularly well-suited for the following positions:

  • As a data engineer, you'll build scalable data pipelines and cloud data platforms
  • As a Cloud Data Engineer, you'll manage Azure-based infrastructure for analytics and AI
  • As an Analytics Engineer, you'll model data using dbt for modern data warehouses
  • As an ETL Developer, you will develop reliable ETL and ELT processes for production environments
Read more
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In this training you will learn:

Azure and Cloud Infrastructure
Apache Spark and Databricks
ETL and ELT Pipeline Engineering
  • Build a scalable cloud data infrastructure on Azure, including data warehouses, data lakes, and lakehouse architectures
  • Designing and Operating ETL and ELT Pipelines with Azure Data Factory, Synapse, Snowflake, and dbt
  • Processing Big Data with Apache Spark and Databricks for Batch and Streaming Workloads
  • Building Data Lake and Lakehouse Architectures with Delta Lake, NoSQL, and Synapse
  • Cloud Fundamentals: Using Linux and Docker Securely and Setting Up Azure VMs, Storage, and IAM
  • Embedding Data Governance Best Practices in Warehouse and Pipeline Design
  • Planning and Implementing a Complete End-to-End Data Engineering Project in the Cloud
Certificate Badge Symbol for award and quality seal.
Certificate Badge Symbol for award and quality seal.
Table of contents

1
Introduction to Data Engineering
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You'll understand the role of a data engineer in comparison to data science and analytics. You'll learn about the data engineering lifecycle, the typical tool stack, and the most important platforms—from orchestration to storage and compute.

2
Data Infrastructure and Cloud
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You are proficient in Linux, Docker, and cloud fundamentals. You will set up Azure VMs, storage, and IAM, and build a simple Azure data pipeline using Synapse or Databricks as part of a mini-project.

3
Data Warehouse and ELT
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You will design cloud data warehouses and operate ELT and ETL pipelines using Azure Data Factory, Snowflake, and dbt. You will apply data governance best practices and build an end-to-end ELT pipeline as part of a mini-project.

4
Big Data, Lake, and Lakehouse
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You'll work with Apache Spark on Databricks for batch and streaming. In the mini-project, you'll build data lake and lakehouse architectures using Delta Lake, NoSQL, and Synapse.

5
Capstone Project
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You will plan and implement a complete end-to-end data engineering project in the cloud. You will choose between an ELT data warehouse, ETL on a data lake, or a lakehouse, and present the architecture, code, and results with support from a mentor.

This training is part of the training programs:
In this training you will learn:
Azure and Cloud Infrastructure
Apache Spark and Databricks
ETL and ELT Pipeline Engineering
  • Build a scalable cloud data infrastructure on Azure, including data warehouses, data lakes, and lakehouse architectures
  • Designing and Operating ETL and ELT Pipelines with Azure Data Factory, Synapse, Snowflake, and dbt
  • Processing Big Data with Apache Spark and Databricks for Batch and Streaming Workloads
  • Building Data Lake and Lakehouse Architectures with Delta Lake, NoSQL, and Synapse
  • Cloud Fundamentals: Using Linux and Docker Securely and Setting Up Azure VMs, Storage, and IAM
  • Embedding Data Governance Best Practices in Warehouse and Pipeline Design
  • Planning and Implementing a Complete End-to-End Data Engineering Project in the Cloud

Your benefits with StackFuel.

100 % Financed

Our training programs are 100% free of charge for you with an education voucher from the Federal Employment Agency.

80 % Practical content

Thanks to the high practical component, you will learn all the skills you need for everyday work in your future data job.

Flexible

Completely online and full or part-time, you can train in the way that works best for you.

Supported by mentors

Our data experts are always in contact and offer support and motivation.

Final certificate

After completing the training program, you will receive our recognized certificate to prove your skills.

Career Service included

Our Career Service supports you with advice and coaching when you start your data job.

The next
start dates.
Training programTraining Date Date/Duration Model
12.10.2026
12.10.2026 7 months Full-time
Full-time Apply
12.10.2026
12.10.2026 14 months Part-time
Part-time Apply
19.10.2026
19.10.2026 7 months Full-time
Full-time Apply
19.10.2026
19.10.2026 14 months Part-time
Part-time Apply
The next
start dates.
Training
Start dates
Data Engineer Data Engineer 12.10.26 +1 more
  • 12.10.2026
    • Full-time - 7 months
    • Part-time - 14 months
  • 19.10.2026
    • Full-time - 7 months
    • Part-time - 14 months
Apply

Here's what our participants have to say:.

Over 8,000 graduates have already completed training in data and AI skills at StackFuel. Here, some of them talk about their experience:

Ninel Kloss
Participant
BI Specialist, Data Analyst, Data Scientist
"During the course, I experienced a lot of positive emotions. The learning process was perfectly organized: there was a lot of important and interesting information, as well as varied and exciting assignments. Not everything I did was always easy for me, but it was always interesting and fun. A special thank you goes to the team of mentors. Whenever you need help, they’re there—patient and professional."
Marco Fischer
Data Scientist
mexxon Group
"The intensive work with important Python libraries and the concepts and mathematical basics taught were very good preparation for my new job!"
Data Scientist Training Program
Ines Bulmahn
Participant
AI & Data Transformation Manager
"The course had a very strong practical component, and I was able to take a lot away from it."
Shahrouz
Participants
Continuing Education for AI Professionals
"The course was well-structured, practical, and explained clearly. The hands-on exercises with Excel, Word, and PowerPoint, as well as the methods for verifying the results, were particularly helpful."
Sebastian Peter Piskalla
Participants
Continuing Education for AI Professionals
"The training is very practical and easy to understand. I especially liked the hands-on project because it allowed me to apply what I had learned right away. The content was clearly structured and very helpful for practical application."
Philipp Buthmann
Participants
Python Programmer
"The overall vibe was just always really great!"
Daniel Hermann
Geodata analyst
GI-CONSULT GmbH
"The competent and friendly lecturers and the examples of content made me enjoy data-driven programming. The certificates (from StackFuel) are a real plus on my CV - and the skills anyway!"
Data Scientist Training Program
Beatrix Bauer
Junior Financial Data Engineer
Telefonica Germany
"With StackFuel, I was able to learn at a time that suits me, at my own pace and in a place where I feel comfortable."
Data Scientist Training Program
Ulrike
Participant
Data Scientist Further Training
"I found the format very helpful because it conveys a lot of knowledge."
Maxi
Participant
BI Analyst Continuing Education
"The mentoring team is always available, and the schedule is flexible."
Georges Kanaan
Participants
Data Analyst Further Training
"The training is very practical and easy to understand. I especially liked the hands-on project because it allowed me to apply what I had learned right away. The content was clearly structured and very helpful for practical application."
Amirhossein Rahimi
Data Scientist
zaplinace GmbH
"The practical, project-oriented approach makes the courses very interesting and has made my learning progress much easier."
Data Scientist Training Program
Philipp Gehrlein
Participants
AI Automation Expert
"I learned a lot of new and practical things during the training that I can now apply directly in my everyday life and in a professional setting."
Lisa Ambrosi de Magistris Verzier
Data Analyst
Interone
"I particularly liked the well-structured curriculum and the clearly conveyed content. I now feel confident in using Python for data analysis without any previous knowledge. The dedicated career service was also a great support."
Data Analyst Training Program
Nurseven Simsek
Participants
BI + Data Analyst
"I really appreciated the well-structured content and the flexible organization."
Farbod Khiawi
Client Operations Consultant / Success Manager
AON
"What I liked best were the regular group sessions with participants and tutors. These were very exciting and beneficial for both learning and motivation."
Data Scientist Training Program
Dr. Pinar Toker
Data Scientist
Eraneos Analytics
"The hands-on, real-world problems at StackFuel helped me master data analysis techniques and Python programming. The focus [...] on industry-relevant skills gave me the confidence and know-how I needed for my job search."
Data Scientist Training Program
Liudmila Litger
Data Analyst
Aviv Group (HomeToGo)
"I was particularly enthusiastic about the practical projects. It was as if I had already gained practical experience before my first day at work."
Data Analyst Training Program
Yeonhee Kim
Participant
BI Analyst Continuing Education
"The live sessions were helpful, as was the support from the mentors."
Ayu Distler
Participant
Python Programmer Training
"I was particularly enthusiastic about the practical projects. It was as if I had already gained practical experience before my first day at work."

Get personal advice now.

We will help you choose the right training program for your data career and advise you on the path to funding.

Free of charge, without obligation and simply over the phone.

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+8,500 graduates
93 % Completion rate
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FAQ

Our training programs are developed and produced by our in-house team of data scientists and subject matter experts, who provide you, as a participant, with personalized mentoring throughout the course. We not only focus on realistic and practical content, but also ensure through one-on-one interaction that all your questions are answered, thereby guaranteeing your learning success. Thanks to our “learning-by-doing“ approach, you’ll learn in our interactive learning environment using realistic datasets and real-world business cases from the industry, perfectly preparing you for a successful career start in a data-related role.
With StackFuel, you’re choosing a market leader with Germany’s most innovative learning platform to develop your data skills in a hands-on way. Through certified training programs, you’ll learn online, on your own schedule, with 80 % of practical content. This will help you successfully transition into a career as a data analyst or data scientist, and you’ll learn how to apply data and the fundamentals of artificial intelligence professionally. Your new career in data starts with your online training at StackFuel.
AI and data have become an integral part of our (professional) lives. Those who understand how to analyze data, use AI tools efficiently, and leverage AI applications possess in-demand skills for the workplace of tomorrow. That’s exactly why people with AI and data skills are particularly valuable to companies—and why new career opportunities are opening up in many industries and professional fields.
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