Overview

The Data Engineering programme at the University of North Texas provides students with the technical expertise required to design and manage sophisticated data architectures. This interdisciplinary Master of Science degree focuses on transforming raw information into high-quality datasets to support modern industrial needs.

Students develop essential skills in building and maintaining robust data pipeline systems while improving overall data reliability and efficiency. The curriculum ensures that graduates can apply advanced algorithms and data structures to solve difficult analytical problems across various professional sectors.

The course is specifically designed for those from science, technology, engineering, or mathematics backgrounds who wish to enhance their programming and engineering capabilities.

Why Data Engineering at the University of North Texas?

The University of North Texas is a prestigious Carnegie-ranked Tier One public research institution, offering students the chance to collaborate with expert faculty on pioneering projects. This status ensures a high-standard academic environment focused on discovery and innovation within the engineering field.

The College of Engineering features state-of-the-art instructional facilities and specialised laboratories equipped with the latest research technology. These top-ranked labs provide an ideal setting for students to explore new frontiers in data management and computational analysis.

Beyond technical training, the programme emphasises professional collaboration and communication skills to meet the evolving demands of the global tech industry. Students may also benefit from teaching and research assistantships, which provide valuable experience alongside financial support through stipends.

Tuition Fee Breakdown

• International fee: USD 16404 per year
• National fee: USD 16404 per year
• Local fee: USD 8700 per year

Visit the Fees and Funding section for a breakdown in your local currency.

Syllabus

The curriculum provides a solid foundation in database systems, big data, and analytical methods. Modules may include:

• Methods in Empirical Analysis
• Scientific Data Visualization
• Database Systems
• Distributed and Parallel Database Systems
• Natural Language Processing
• Big Data and Data Science

Careers with Data Engineering

Graduates are prepared for immediate entry into one of the fastest-growing sectors in technology, where demand for skilled engineers consistently outpaces supply. The programme equips students with the marketable skills needed to excel in diverse industries that rely on large-scale data infrastructure.

Common career paths for those completing this degree include roles such as data engineers, data architects, and business intelligence architects. Additionally, graduates often find success as machine learning engineers or data warehouse developers within global organisations.

The training provided ensures that alumni can effectively communicate technical information and adapt quickly to emerging technologies. These competencies make them highly sought after by employers looking to improve data quality and operational efficiency through advanced engineering solutions.