Hasso-Plattner-InstitutSDG am HPI
Hasso-Plattner-InstitutDSG am HPI

Master of Science: Data Engineering

Program overview

  • Title: Data Engineering
  • Degree: Master of Science
  • Standard length of studies: 4 semesters
  • Credits: 120
  • Language of instruction: German (DSH 2)
  • Start of studies: Summer + Winter Semester
  • Application deadline 2021: December 1st / June 1st
  • Costs: No tuition (only University of Potsdam's semester fees)
  • Flyer (german only)


Highly qualified IT engineers are in great demand worldwide for analyzing the growing volumes of data in all areas of society. The master’s program in data engineering is aimed at the next generation of highly talented IT engineers who wish to complete a practical and research-oriented computer science study program and to focus on big data systems; that is, the collecting, linking and analyzing of large and complex data volumes.

Have you already completed a bachelor’s degree in the field of computer science, mathematics, IT system engineering, data engineering or in a related subject area? Would you like to undertake a practical and research-oriented computer science study program? Then we look forward to your application!

We enable students to learn in small groups with the special supervision of our professors. It is possible to begin the study program in the summer and in the winter semester. The eligibility of applicants is determined by the Admissions Committee of the Hasso Plattner Institute.

Career Prospects for Master’s Degree Graduates

Graduates of the master’s program earn an invaluable professional qualification. They are able to take on leadership or management positions, particularly where the design, building, maintenance, and operation of complex information systems play a key role. Upon graduation students are ready to assume the position of data engineer, data scientist, data specialist or strategic data analyst.  

Study Content

The Master of Science in Data Engineering is a four-semester program at the Faculty of Digital Engineering, a faculty jointly founded by the Hasso Plattner Institute (HPI) and the University of Potsdam (UP).

In their studies, students deepen the scientific foundations of computer science and acquire theoretical, methodical and practical skills to deal with complex information systems. The focus thereby is on the core areas of data management, data analysis, and data visualization. Focused on actual problems from industry and research, students learn to map the real process of a data-driven project.

Besides receiving in-depth knowledge of IT technology, students achieve competency in so-called soft skills, which play a vital role in the successful management of large IT projects. 

Module Groups

The master’s program has a flexible and individualized structure. Students can choose from a wide range of subjects and tailor the program to fit their individual needs and career goals.

An overview of all modules of the master's program Data Engineering can be found here(Geman only)

Compulsory Modules

  • DE-A Module Data Analysis
    This module shows the limits of fundamental data analysis methods and teaches in-depth methods and concepts of different data analysis paradigms in the areas of supervised learning, unsupervised learning, statistical data analysis, as well as interactive data exploration.
  • DE-S Module Big Data Systems
    Big data systems master the acquisition, processing and storage of data through new technologies for extensive data (volume) from heterogeneous sources (variety) with a high acquisition frequency and a fast processing time (velocity).
  • DE-M Module Data Management
    This module teaches the architectures and methods for the distributed parallel processing of data as established concepts for the mastery of big data. Moreover, it provides fundamental contents on data management tasks such as data collection, data preparation, data transformation and data validation.
  • DE-V Module Data Visualization
    In this module, the tasks and goals in the field of information visualization are defined and the concepts and methods of visualization conveyed. These include graphical primitives, visual variables, and dimensions of visualization and presentation forms for information.
  • DE-EG Module Ethics and Society
    This module addresses ethical questions, for example the relationship of state to citizen and of company to citizen, particularly under the aspect of modern data processing. The objective is to be able to ethically evaluate conflict situations in business and society and to preventively avoid such situations.
  • DE-RWM Module Law Economics and Management
    This module teaches legal and economic issues that are relevant in the creation and distribution of software products and the founding and management of IT companies. Key topic areas are intellectual property rights, software contract law as well as software licensing law.
  • DE-L Module Data Engineering Lab
    In the data engineering lab, a team of students work on a selected, research-oriented question related to big data systems from one of the Hasso Plattner Institute’s Research Groups. The question is analyzed and then for a sub-area a solution is designed, constructively implemented and scientifically documented.

 Specialization Areas

  • Data Analytics
  • Data Preparation
  • Data Security
  • Scalable Data Systems
  • Complex Data Systems

Soft Skills

  • Communication
  • Management and Leadership
  • Design Thinking Basic Track 
  • Design Thinking Advanced Track

Master Project


Scope of the Master’s Program

In order to earn a Master’s degree 120 credits are required

  • 48 credits in the module group Data Engineering
  • 2 specialization areas with 3 modules each (totaling 36 credits) :
    - Concepts and methods
    - Techniques and tools
    - Specialization
  • 6 credits in soft skills modules
  • 30 credits for the master’s project

You can find information on the application and selection procedure, and on the current study and exam regulations at the site Application to the Master’s Program.

Model Curriculum: Master Data Engineering


Further information on application as well as study and examination regulations can be found on the page Application for the Master's Program.

Important Links