Data Engineering (MSc)

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.

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. Companies and institutions in almost every domain need:

• Experts for data acquisition who find out how to collect the data needed;
• Experts for data management who know how to store, enhance, protect and process large amounts of data efficiently;
• Experts for data analysis who evaluate and interpret the collected data correctly and are able to visualize the findings clearly.
• Graduates of the program work as data analysts, data managers, data architects, business consultants, software and web developers, or system administrators;

A MSc degree in Data Engineering also allows students to move on to a PhD and a career in academia and research institutions.

The employability of Data Engineering graduates is promoted by organizing contacts with industry and research institutes throughout the curriculum. In the first semester, in the Current Topics in Data Engineering seminar, companies and research groups introduce their field of interest. The advanced projects, in the second and third semester can be combined with internships in research institutes or companies. In the second and third semester, the participation in public big data challenges is organized as integral part of the curriculum.