Master in Data Engineering

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.

• 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.

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 Data Engineering program is embedded in the School of Computer Science and Engineering. Its interdisciplinary nature is taken into account by including courses from the School of Science and the School of Business, Social & Decision Sciences and Advanced Projects in research groups in all schools oncampus are an integral part of this study program.

Core Area(45 CP)

This area is the centerpiece of the Data Engineering program. The nine mandatory modules in the Core Area cover essential methods of data engineering. They provide the foundations for further, more advanced courses and applied projects by introducing the fundamental concepts, methods and technologies used in data engineering. The modules are intensive courses accompanied by hands-on tutorials and labs.

To pursue a DE master, the following Core modules (40 CP) need to be taken as mandatory modules (m):

• CORE Module: Data Management and Databases (m, 5 CP)
• CORE Module: Data Analytics (m, 5 CP)
• CORE Module: Python Programming for Data Engineering (m, 5 CP)
• CORE Module: Cloud Computing (m, 5 CP)
• CORE Module: Data Pipeline Engineering (m, 5 CP)
• CORE Module: Data Security and Privacy (m, 2.5 CP)
• CORE Module: IT Law (m, 2.5 CP)
• CORE Module: Data Warehousing: Concepts and Technologies (m, 5 CP)
• CORE Module: Image Processing for Data Engineers (m, 5 CP)

Elective area (25 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 can choose to strengthen their knowledge in elective modules in the area of Computer Science, Geo-Informatics, Bio-Informatics, Business & Supply Chain Engineering and Mathematics. These modules can also serve as preparation for the Advanced Projects or the Internship within the Discovery Area and for the Master Thesis. 

The following mandatory elective (me) modules can be chosen in the Elective Area: 

• Big Data Challenge (me, 5 CP)
• Machine Learning (me, 5 CP)
• Data Acquisition Technologies and Sensor Networks (me, 5 CP)
• Principles of Statistical Modeling (me, 5 CP)
• Advanced Databases (me, 5 CP)
• Network Theory (me, 5 CP)
• Geo Informatics (me, 5 CP)
• Modeling and Analysis of Complex Systems (me, 5 CP)
• Management and Analysis of Biological and Medical Data (me, 5 CP)
• Data Mining (me, 5 CP)
• Data Analytics in Supply Chain Management (me, 5 CP)
• Modeling and Control of Dynamical Systems (me, 5 CP)

In addition to these elective modules, up to one relevant module from other graduate programs and up to one 3rd year modules from the undergraduate curriculum at Constructor University can be taken after consultation with the academic advisor and with the approval of the program coordinator. 

Particularly relevant elective modules from other graduate programs include

• Text Analysis and Natural Language Processing (DSSB, me 5CP)
• Deep Learning (CSSE, me 5CP)

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.

The following remedial modules can be chosen in the Elective area:

• Calculus and Linear Algebra for Graduate Students (me, 5 CP)
• Probabilities for Graduate Students (me, 5 CP) 

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.

The following remedial modules can be chosen in the Elective area:

• Calculus and Linear Algebra for Graduate Students (me, 5 CP)
• Probabilities for Graduate Students (me, 5 CP) 

Discovery area (15 CP)

This area introduces the students to Current Topics and Challenges in Data Engineering already in the first semester with lectures taught by faculty members and invited experts from external research institutes and companies, who present selected fields of their research and interest in data engineering. The students then choose projects or internships on such topics of current interest in the second and third semester allowing them to apply data engineering methods to practical, real-life tasks.

The following module is mandatory (m) in the Discovery area: 

• Discovery Module: Current Topics in Data Engineering (m, 5 CP)
• The following modules are mandatory elective (me) in the Discovery area:
• Discovery Module: Data Engineering Advanced Project t I (me, 5 CP)
• Discovery Module: Data Engineering Advanced Project II (me, 5 CP)
• Discovery Module: Data Engineering Advanced Internship (me, 5 CP)

Career area (10 CP)



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

The following modules are mandatory (m) for the career area: 

• Career Module: Language (m, 2.5 CP)
• Career Module: Communication & Presentation Skills for Executives (m, 2.5 CP)
• Career Module: Academic Writing Skills / Intercultural Training (m, 2.5 CP)
• Career Module: Ethics and the Information Revolution (m, 2.5 CP)

Master thesis (30 CP)



In the fourth semester, students conduct research and write a mandatory master thesis guided and supported by their academic supervisor, worth of 30 credit points.

• 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. 

All applicants must show an adequate command of the English language to enroll at Constructor University. An applicant’s English language ability (non-native speakers) may be demonstrated through language proficiency test scores.

You will qualify for an English proficiency waiver if you:

are a native English speaker OR

have been instructed exclusively in English for a minimum of 6 years OR

have scored 600 or higher on the Evidence-Based Reading and Writing section OR

have scored 9 or higher on the ACT Writing section

English Language proficiency tests accepted by Constructor University and the minimum scores/grades:

• TOEFL (Paper-based): Minimum Score: 575

• TOEFL (Internet-based): Minimum Score: 90

• MELAB (Michigan Test): Minimum Score: 80

• IELTS (British Council): Minimum Score: 6.5

• GCSE (British General Certificate of Secondary Education): Minimum Score: A or B

• Cambridge Certificate of Proficiency in English (CPE): Minimum Score: A, B, C and C1 pass

• Cambridge Certificate in Advanced English (CAE): Minimum Score: A, B, C

• Cambridge First Certificate in English (FCE – extended): Minimum Score: A

• International Baccalaureate English A Lit / Lang & Lit: Minimum Score: 6, 7

• SAT Evidence-Based Reading & Writing: Minimum Score: 600

• ACT Writing: Minimum Score: 9

• Duolingo English Test: Minimum Score: 110

• Pearson PTE Academic: Minimum Score: 58