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Master of Science - Graduate Program


Data Engineering - The Program

The graduate program in Data Engineering offers a fascinating and profound insight into the methods and technologies of this rapidly growing area.

The program combines big data aspects of “Data Analytics” as well as of “Data Science” with the technological challenges of data acquisition, curation, and management.

Thus, the program provides the essentials for paving the way to a successful career: computer skills and mathematical understanding paired with practical experience in selected application fields. The Data Engineering program attracts students with diverse career goals, backgrounds, and prior work experience.

Therefore, the program offers four focus tracks within which the students can choose to specialize further: Computer Science, Geo-Informatics, Bio-Informatics, and Business & Supply Chain Engineering. These tracks are a preparation for the Advanced Projects within the Discovery Area and the Master Thesis.

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Career Perspectives

Demand for Data Engineers is massive. Typical fields of work encompass the finance sector, the automotive and health industry as well as retail and telecommunications.

Key Facts

Program Start Date 2022:

last week of August (orientation week), first week of September (classes)


€ 20,000 per academic year


All students are considered for an academic achievement scholarship based on their school grade point average (GPA).
EU students are eligible for a minimum guaranteed scholarship of € 4.000.

Application Deadlines 2022:

June 1 (global) and July 15 (for applicants who do not need a visa)


2 years full-time


Financing Options:

Each admitted candidate will receive an individual financial package.



Today we are “drowning in data and starving for information” while acknowledging that “data is the new gold”. However, deriving value from all the data now available requires a transformation in data analysis, in how we see, maintain, share and understand data.

Data Engineering is an emerging profession concerned with the task of acquiring large collections of data and extracting insights from them. It is driving the next generation of technological innovation and scientific discovery, which is expected to be strongly data-driven.

The program is embedded in the “Mobility” focus area at Jacobs University. This focus area investigates the mobility of people, goods, and information. Even though the Data Engineering program is centered in “Mobility”, it includes contributions from and supports applications in the two other research foci: Health (bioactive substances), and Diversity (in modern societies).

Four program tracks to allow specialization:
Moreover, the Data Engineering program attracts students with diverse career goals, backgrounds, and prior work experience. Therefore, the program offers four focus tracks within which the students can choose to specialize further:

  • Computer Science,
  • Geo-Informatics,
  • Bio-Informatics
  • Business & Supply Chain Engineering.

These tracks are a preparation for the Advanced Projects within the Discovery Area and the Master Thesis.

Computer Science Track: In particular, Computer Science provides students with the skills to go beyond a mere usage of existing toolboxes and to develop innovative data analysis techniques of their own design.

Geo-Informatics Track: It gives students an introduction to Geographic Information System techniques, principles of spatial analysis, and data mining with integration of remote sensing and GPS. It thereby provides an early exposure to earth science data and its handling.

Bioinformatics Track and the analysis of biomedical data: Integration and model-based interpretation of high-throughput data are severe bottlenecks in biomedical and pharmaceutical research. Data Engineering prepares students for the novel computational challenges in these fields.

Business & Supply Chain Engineering Track: Students can also choose the specialization track in Business & Supply Chain Engineering. A vast amount of data is collected as part of business processes in particular along supply chains. In this specialization track, students will concentrate on the full data analysis cycle including pre-processing of data, data analysis and deployment of model results within the business process.

Study program structure


The Data Engineering graduate program is composed of foundational lectures, specialized modules, industry seminars and applied project work, leading to a master thesis that can be conducted in research groups at Jacobs University, at external research institutes or in close collaboration with a company. The program takes four semesters (two years). The following table shows an overview of the modular structure of the program. The program is sectioned into five areas (Core, Elective, Methods, Discovery, and Career) and the Master Thesis. All credit points (CP) are ECTS (European Credit Transfer System) credit points. In order to graduate, students need to obtain 120 CP.

Elective Area (15 CP)

The Data Engineering program attracts students with diverse career goals, backgrounds, and prior work experience. Therefore, modules in this area can be chosen freely by students depending on their prior knowledge and interests.

Students may choose any combination of the modules listed below. Each track may be followed completely and/or complemented with other modules (as necessary in case of the tracks with 10 CP).

Methods Area (15 CP)

In the Methods Area advanced concepts, methods and technologies of data engineering are introduced with a view towards industrial applications. Students can choose freely from the modules in this area. To enhance flexibility, students may transfer modules between the Elective and the Methods Areas (except for remedial modules) after consulting their academic advisor.

Within the Methods Area Jacobs University offers special remedial modules, which are recommended to refresh knowledge or to fill knowledge gaps, preparing students to successfully take the Data Engineering Core Area modules. Based on a placement test in the orientation week, the academic advisor will propose which of the modules are useful depending on prior knowledge of the student.

Discovery Area (15 CP)

This area features in the first semester a Project Seminar introducing the students to Current Topics and Challenges in Data Engineering, which is followed by two advanced projects in Data Engineering in semesters 2 and 3, each worth 5 CP. The projects can be done in the research groups at Jacobs University or during internships in companies. The projects are supervised by Jacobs University faculty.

Career Area (15 CP)

In this area students acquire skills preparing them for a career as data engineers in industry.

Master Thesis (30 CP)

In the fourth semester, students conduct research and write a master thesis guided and supported by their academic advisor.




Erin Doby
Recruitment Counselor Graduate Students

graduateadmission [at]
Phone: +49 421 200 4204

 Do you have any questions or need consultation?
Call us or write us – we are happy to help you with your inquiry.



1 Start 2 Complete


The Data Engineering graduate program is targeted towards students who have completed their BSc in areas like computer science, physics, applied mathematics, statistics, electrical engineering, communications engineering or related disciplines, and who want to deepen their knowledge and proceed to research-oriented work towards a master or ultimately a PhD degree.

Teaching approach

The program aims to provide an in-depth understanding of the essential aspects of data-based decision making and the skills required to apply and implement these powerful methods in a successful and responsible manner. Apart from the necessary programming skills, this comprises:

  • Methods of data acquisition both from the internet and from sensors;
  • Methods to efficiently store and access data in large and distributed data bases;
  • Statistical model building including a wide range of data mining methods, signal processing, and machine learning techniques;
  • Visualization of relevant information;
  • Construction and use of confidence intervals, hypothesis testing, and sensitivity analyses;
  • The legal foundations of Data Engineering;
  • Scientific qualification;
  • Competence to take up a qualified employment in Data Engineering;
  • Competence for responsible involvement in society;
  • Personal growth.
Students & Alumni

I think this is a degree with a promising future – whether it is in industry or research.

Moises Daniel Garcia Rojas

Understanding the worldwide flow of people, goods, and information is important in today’s globalized world. Information influences the life of the individual and the cohesion of societies and cultures in many different ways.
Department Computer Science & Electrical Engineering
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