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Data Engineering

Data Engineering

Data Engineering
Master of Science - Graduate program
The program

This study program belongs to the School of Computer Science & Engineering

Location: On Campus

The curriculum of the Data Engineering program provides students with a comprehensive understanding of the big data aspects of data analytics and data science, with the technological challenges of data acquisition, curation, and management.

The program focuses on the application of computer skills and mathematical knowledge to solve real-world problems in different industries. It appeals to students who completed their BSc in areas like computer science, physics, applied mathematics, statistics, electrical engineering, communications engineering, or related disciplines, and offers four focus tracks: Computer Science, Geo-Informatics, Bio-Informatics, and Business & Supply Chain Engineering.

These tracks prepare students for advanced projects and their master's thesis, giving them hands-on experience in their area of interest. The program is well-rounded, providing students with theoretical knowledge and practical experience, giving them the tools to succeed in this rapidly growing field.

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Interested in the program?
Key facts
Program Start Date 2025:
last week of August (orientation week), first week of September (classes)
Application Deadlines 2025:
July 31st
Tuition:
€ 20,000 per academic year
Duration:
2 years full-time
Scholarships:
All students are considered for an academic achievement scholarship based on their school grade point average (GPA).
Financing Options:
Each admitted candidate will receive an individual financial package.
5 Reasons to join this program:
  • Specialized Tracks for Diverse Career Goals: Choose from four industry-aligned focus tracks to tailor your expertise for specific fields like biomedical research, spatial analysis, or supply chain optimization.
  • Integration of Big Data and Engineering: The program combines advanced techniques in data analytics with practical solutions for data acquisition, curation, and management.
  • Hands-On Learning with Advanced Projects: Engage in real-world applications through capstone projects, internships, and participation in public big data challenges.
  • Interdisciplinary Applications: Collaborate across fields such as computer science, natural sciences, and business, gaining insights into how data engineering drives innovation.
  • Industry-Driven Curriculum: Benefit from seminars led by industry professionals, networking opportunities, and strong connections to leading companies.
Students
Rankings
#1
International university in Europe (THE 2023)
#1
private university in Germany (THE 2023)
93%
Job success within a year (Alumni survey)
100+
Student clubs, 1 campus
Program Overview

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 Constructor 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).

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 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.

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

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Study program structure

Curriculum

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DE Study Scheme Fall 2024

 

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 Constructor 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).

program structure

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.

program structure

Within the Methods Area Constructor 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.

program structure

 

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 Constructor University or during internships in companies. The projects are supervised by Constructor University faculty.

program structure

Career area (15 CP)

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

program structure

Master thesis (30 CP)

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

program structure

Data Engineering (MSc) program handbook Fall 2024
Data Engineering (MSc) program handbook Fall 2023
Data Engineering (MSc) program handbook Fall 2022
Data Engineering (MSc) program handbook Fall 2021

 

 

 

All study programs at Constructor University are accredited by the German Accreditation Council, guaranteeing adherence to high academic quality and international standards. This accreditation confirms that each program meets formal and subject-related criteria in terms of content, structure, and intended learning outcomes.

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How to apply

Join Constructor University in 5 easy steps:

  1. Complete your application
  2. Receive your decision after 3-4 weeks
  3. Learn about financing options
  4. Enroll and pay your deposit
  5. Settle in during O-Week and start your studies

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Graduation
Financing

Discover all the information you need about our fees and financing options for Constructor students. Our dedicated Student Financial Service Team will assist you in finding the best financial solution that will enable you to pursue your desired program and create a successful career path.

Cost of attendance 2025 / 2026
The direct costs of attendance include tuition, room and board, and fees, as outlined below.

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Career perspectives
  • 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 are in demand for experts in data acquisition, management, and analysis.
  • The employability of Data Engineering graduates is promoted by organizing contacts with industry and research institutes throughout the curriculum.
  • Internships in research institutes or companies, as well as public big data challenges fostering students’ practical skills in the second and third semester.
  • 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. 
CLAMV
Study Program Chair
Associate Professor of Complex Systems
Associate Professor of Medical Cognitive Computing
Ready for your future?
Why Study at Constructor University
International experience
Train your intercultural skills by studying with talents from more than 120 countries and excellent study abroad options.
Top rankings
Benefit from highest standards in teaching, interdisciplinary learning, early research involvement, and hands-on education.
Global career
Connect with Alumni to broaden your professional network & start your career with our individual career service support.
School of Computer Science & Engineering

The study program Data Engineering is part of the School of Computer Science & Engineering.

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.

Expertise in different disciplines, such as computer science, communication technology, logistics, mathematics and psychology are brought together in the development of new solutions.

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Constructor University Spring 2024
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Life on campus

Become part of a global community

Constructor University Students come from all over the world to live and learn at Constructor University. Our student body represents 120 nations. They form an ambitious campus community whose internationality is unprecedented in Europe. Constructor University’s green and tree-shaded 80-acre campus provides much more than buildings for teaching and research.

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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.
Contact us

Get in touch - let your future start at Constructor University

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

Graduate FAQ

For PhD Degrees please contact:

Dr. Svenja Frischholz

Head of academic advising services

sfrischhol@constructor.university

Phone: +49 421 200 4338

 

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