Program Overview

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MSc Data Engineering

Overview

Data engineering is a major growth area within both the commercial and public sectors, and there is a recognised shortage of professionals that have the required range of Data Engineering knowledge and skills. This online MSc Data Engineering programme addresses this shortage.

The programme is aimed at graduates and practitioners with a background in business, quantitative science, or computing who wish to develop into effective Data Engineers with the business understandings and analytical, statistical, and computing skills to contribute to this vital area for contemporary commercial and public sectors.

Edinburgh Napier University has excellent research and knowledge transfer links with many local, national and international organisations in Data Engineering related areas. This will give candidates the best possible chance at securing one of the many available data engineering jobs.

The acquisition of knowledge and skills on the programme will give students a critical understanding of the tools and technologies involved in the analysis, design, development, testing, evaluation and modification of Data Engineering solution; enable them to select and evaluate appropriate tools for the collection, processing and presentation of complex and diverse data sets, and critically review an organisation’s data needs and make appropriate and measurable recommendations on the use of Data Engineering techniques.

If you are a junior data engineer looking to move into a more senior role, or someone who wants to become a data engineer from a different profession, this course is for you.

Delivered online (part-time), this MSc is ideally suited to individuals who intend to balance their personal and professional commitments with their studies.

This programme was developed and in partnership with and partially financed by The DataLab.

Mode of Study:

• Online learning
• Part-time

Duration:

• 21-33 months

Start date:

• June
• January
• September

Course details

You will study the software engineering process in both creating and working with large and complex data sets, acquiring the knowledge and experience of tools and techniques that are necessary to be a successful Data Engineer in a range of environments. The focus of the programme is on the practical application of these skills and tools, with the underpinning theories used within this context.

Learning, teaching and assessment methods focus on providing students with engaging and contemporary materials that link theory to practice and require students to take a critical perspective on both.

The programme will benefit people wanting either to change career and start working in data solution development, or to upskill from being a software engineer or data scientist to the combined role of Data Engineer. As the programme is paced to suit the learner, the MSc in Data Engineering will also support learners coming back to education.

Your final dissertation project will allow you to use the tools and approaches you have developed during the course.

You can pay for this course flexibly on a module-by-module basis. This means that you don't have to pay the full course cost upfront.

What you study

• Data Management and Processing
• Data-Driven Decision Making
• Business Intelligence and Reporting for Enterprises
• Data Wrangling
• Database Systems
• Data Analytics
• Master's Dissertation (60 credits)

The Master's Dissertation is studied over two trimesters following successful completion of all other modules.

For the award of MSc Data Engineering, you must successfully pass all seven modules, giving a total of 180 credits. All modules are 20 credits, except where otherwise indicated.

Within each trimester, whilst there is flexibility to work through the material at your own pace you need to be aware of the assessment dates as there is no flexibility in these.

If there is any question regarding the authorship of any submitted assessments, we reserve the right to require students to undertake an online viva.

How you’ll be taught

This course is delivered fully online. You can choose from three start dates (September, January, May) and typically takes between 21 – 33 months to complete, subject to your pace of study and module availability. You’ll study seven modules in total, with a maximum of two modules each trimester where available.

Entry requirements

Year 1

The entry requirement for this course is a Bachelor (Honours) Degree at a 2:2 or above in an appropriate field, for example, software development, computing, or business analytics. Alternatively, other qualifications or experience that demonstrate through our recognition of prior learning process that you have appropriate knowledge and skills at SCQF level 10 may be considered. We may also consider lesser qualifications if you have sufficient professional work experience within the industry.

There will also be a selection interview for this course. Competition for places varies from year-to-year and achievement of the typical minimum entry requirements does not always guarantee shortlisting for interview or a place on the course.

To succeed on our Global Online degrees you must have access via computer or laptop to view and download written and video content. You will also need basic IT skills that enable you to write and edit document, send and receive email, find your way around our online learning environment and search for and access online learning resources, download files and use online forums.

English language

If your first language isn't English, you'll normally need to undertake an approved English language test and our minimum English language requirements will apply.

This may not apply if you have completed all your school qualifications in English, or your undergraduate degree was taught and examined in English. Check our country pages to find out if this applies to you.

International students

We welcome applications from students studying a wide range of international qualifications.

Admissions policies

We’re committed to admitting students who have the potential to succeed and benefit from our programmes of study.

Our admissions policies will help you understand our admissions procedures, and how we use the information you provide us in your application to inform the decisions we make.

Fees & funding

The course fees you'll pay and the funding available to you will depend on a number of factors including your nationality, location, personal circumstances and the course you are studying. We also have a number of bursaries and scholarships available to our students.

Tuition fees for 2024/25

2024/25	2025/26
UK Students	£820	£855
Overseas Students	£835	£870

Modules for your course can be purchased through our online store and must be paid in full at the time of enrolment. You will purchase modules in advance of each trimester of study. The fee listed above applies to 20 credits. Please note, the full course comprises of 120 credits in total for BA/BSc (top-up) and 180 credits in total for MSc. Please note that you will pay the module fee according to the academic year in which you study each module, meaning that the total cost of your course will vary depending on the year in which modules are undertaken. If you are paying a fixed programme fee through one of our global partners, the cost will be no higher than if you were buying modules directly from our online store.

Tuition fees are subject to an annual review and may increase from one year to the next. For more information on this and other tuition fee matters, please see our Fees and Funding links above.

Careers

What can you do with a MSc Data Engineering degree?

In an era driven by data, the ability to harness and manipulate information is essential for driving innovation and making informed decisions. Our programme offers a deep dive into the world of data engineering, equipping you with the skills and knowledge needed to design and implement robust data infrastructure and systems. Participation in this course will support your aspirations either to change career or start work in the area of Data Engineering. Upon graduating form our Data Engineering courses you’ll be able to work in a variety of positions, including:

• Machine Learning Engineer
• Big Data Engineer
• Data Scientist
• Data Modelling

Throughout the course, you'll explore a wide range of topics, from data management and processing to business intelligence and reporting for enterprises. Through hands-on projects and real-world case studies, you'll gain practical experience working with large-scale datasets and cutting-edge technologies, preparing you to tackle the complex challenges of data engineering.

Upon completion of the program, you'll emerge as a skilled and adaptable data engineer, ready to leverage the power of data to drive business success and societal impact. Whether you aspire to work in data-driven organizations, research institutions, or tech startups, our MSc in Data Engineering will provide you with the expertise and confidence to excel in the rapidly evolving field of data engineering.

What does a Big Data Engineer do?

Working as a Big Data Engineer, your expertise in managing and analyzing vast volumes of information will unlock insights and drive decision-making at a scale. In this role, you'll be responsible for designing, building, and maintaining the infrastructure and systems that enable organizations to process and extract value from large datasets.

You will be architecting data pipelines that collect, store, and process data from various sources, ensuring scalability, reliability, and efficiency. From data ingestion and storage to data processing and analysis, your days will be filled with designing and optimizing solutions that empower stakeholders to derive actionable insights and make informed decisions.

As a Big Data Engineer, you'll work closely with data scientists, analysts, and business stakeholders to understand data requirements and translate them into scalable and performant solutions. Whether you're working with structured or unstructured data, your expertise in distributed computing, parallel processing, and data modeling will be instrumental in turning raw data into valuable insights.