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Deutsch Who is the Master Data Engineering Technologies programme suitable for?
The Master's degree programme Data Engineering Technologies is aimed at university graduates from computer science, physics, mathematics, statistics, electrical engineering, communication technology or related fields. You are in the right place if you want to deepen your knowledge in data-driven technologies and develop it in a practice-oriented way – whether for direct application in industry or with the goal of pursuing a doctorate. It is particularly aimed at those interested in pursuing a career in the field of Data Engineering, Data Science or related IT specialisations.
Admission requirements for enrolment
The formal requirements for admission to the Data Engineering Technologies Master of Science at Constructor University are:
- Completed Bachelor's degree in computer science, physics, applied mathematics, statistics, electrical engineering, communication engineering or a comparable discipline.
- Proof of English language skills through a recognised language test: at least 90 points in TOEFL, 6.5 in IELTS or 110 in the Duolingo English Test.
- Letter of motivation demonstrating your subject-related interest and goals in the field of Data Engineering.
- Curriculum vitae (CV).
- Bachelor's degree certificate and official university transcripts (certified copies).
- Copy of a valid passport.
- Reference letters are optional but can strengthen your application.
Personally, you should have strong analytical and problem-solving skills. You are also expected to be willing to proactively engage with complex technological issues and to contribute your communication skills, for example in project work or presentations.
What content and skills does the Master’s degree in Data Engineering Technologies impart to you?
In the Master’s programme Data Engineering Technologies, you will acquire comprehensive subject knowledge to help shape data-driven innovations and modern information systems. The programme deepens key areas such as Big Data Analytics, Data Management, and Cloud Computing. You will develop the following competencies:
- Data acquisition: Methods for capturing and integrating large datasets from the internet or sensors.
- Data management: Efficient and secure storage of data in distributed databases and data warehouses.
- Statistical modelling & data mining: Application of modern analytical methods, signal processing, and machine learning.
- Data visualisation: Preparation of complex datasets to support decision-making.
- Machine learning & deep learning: Building and training models for classification, regression, and forecasting.
- Statistics and analytical methods: Hypothesis testing, sensitivity analyses, and working with confidence intervals.
- Law and data protection: Legal frameworks, data security, and ethical aspects of digitalisation.
- Interdisciplinary work: Linking data science with application fields such as business, social sciences, engineering, and natural sciences.
- Scientific & communicative competence: Conducting independent research projects, analytically presenting results to different target groups.
You will learn to critically assess technical innovations, develop your own solutions for real data-driven application problems, and reflect on the societal and ethical consequences of data-driven decisions.
How is the part-time distance learning course Data Engineering Technologies structured?
The online programme spans four semesters (120 ECTS), is fully digital, and offers you maximum temporal and spatial flexibility. The course structure is as follows:
- Synchronous & asynchronous formats: You independently work through study materials (e.g. videos, case studies, podcasts) in the learning management system. Additionally, you take part in virtual seminars and tutorials.
- Support: Subject lecturers and experienced tutors accompany you individually. Interaction with fellow students takes place in online groups.
- Practical relevance: Hands-on projects, case studies and, if applicable, optional internships with IT partner companies of the Constructor network are integral components.
- Degree: The course concludes with the award of a Master of Science; the graduation documents are issued in physical form. Academic achievements are assessed through module exams, project work, and, if applicable, a master’s thesis.
Thanks to the targeted mix of interactive live elements and independent learning phases, you can optimally tailor the programme to your professional and personal commitments.
What career opportunities does the MSc Data Engineering Technologies open up for you?
The demand for Data Engineers and data experts is growing strongly across industries. With the Master’s degree, a variety of career paths open up for you, for example:
- Data Engineer or Data Architect in companies across various sectors (finance, energy, automotive, healthcare, retail, telecommunications)
- Data Analyst or Data Manager: Planning, management, and analysis of large datasets in organisations
- Business Consultant specialising in data strategy
- Software & web development, especially in the context of data-driven applications and cloud solutions
- System administrator with a focus on big data architectures
- Research & academia: Opportunity to pursue a doctorate (PhD) and work at universities or research institutes
The Constructor network supports you in securing internships and promotes your networking with global companies. According to surveys, over 93% of graduates find suitable employment within one year of completion.
How much does the Data Engineering Technologies distance learning programme cost and how can you finance it?
The total cost for the four-semester distance learning course amounts to 10,000 euros (2 x 5,000 euros tuition fees per academic year). The fee includes all digital learning materials, use of the learning management system, and personal support from the Constructor team.
Important note: Currently, there are no scholarships, no tuition fee deferrals, and no needs-based funding options directly through the university for this online programme. External funding, for example through an employer or tax deductibility as training expenses, can be examined on a case-by-case basis.
Travel costs, in particular for optional participation in the graduation ceremony in Bremen, are not included in the tuition fees.
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