Assistant Professor; Teaching Focussed in Data Engineering & Applied Analytics

About The Role

We are seeking to appoint an Assistant Professor (Teaching-Focused) with experience of developing or delivering modules or skills in the field of Data Engineering and Applied Analytics.

The successful candidate will have a developing professional or academic experience in building and teaching data analytics and machine learning pipelines and play a role in developing modules in areas of relevance to WMG.

We are particularly interested in applicants with knowledge and teaching experience in:

• Data engineering concepts and data pipeline development.
• Data analytics and applied data science methods.
• SQL and No
  
  SQL databases.
• Big data technologies (e.g. Apache Spark or similar).
• Cloud-based data platforms (e.g. AWS, Azure, GCP).
• Building and deploying data analytics or machine learning solutions in applied settings.

This role is on the University of Warwick Teaching Career Pathway, providing opportunities for advancement up to and including Professor level.

This is an education focused appointment and we are looking for candidates who can demonstrate experience of teaching in higher education and a passion for impactful education and positive student outcomes. Candidates with a track record in research outputs but limited educational experience are unlikely to be shortlisted for this role.

There is significant growth in demand for our education programmes and this is an exciting opportunity for you to develop your professional profile and work as part of a world‑renowned education group. In return we will provide a great range of benefits which includes membership of the USS pension scheme, 30 days holiday plus bank holidays and Christmas closure, and excellent learning and development opportunities.

• For an informal conversation about this role contact Dr Awinder Kaur, Head of Digital Technologies and Machine Intelligence (DTMI) Education Group,

The role will suit individuals with a passion for applied, industry-focused education, and those who teach technical content in practical and engaging ways. You will have opportunities to shape content that prepares students for careers in data engineering, data analytics, and data driven innovation.

For roles at Assistant Professor level the successful candidate will hold a doctorate, or equivalent professional qualification alongside a postgraduate degree, and have experience of teaching in a higher education context.

WMG is the largest department at the University of Warwick with over 900 staff, world renowned for providing innovative solutions to industry through its research, development and education programmes. Our industry focussed education portfolio includes nearly 3,000 students studying management, technology and applied engineering subjects, at postgraduate and undergraduate level. We have high expectations for our teaching and our courses are regularly ranked top in the UK and amongst the leading courses in their field in the world.

At WMG we are committed to supporting staff to achieve their potential. We currently hold the Athena SWAN Silver Award, and the University of Warwick holds an Institutional Silver Award: a national initiative that recognises the advancement of gender equality, representation, progression and success for all in academia. We are supportive of staff with caring responsibilities including a generous maternity/paternity/adoption/parental leave policy, and onsite childcare facilities.

We will consider applications for employment on a part-time or other flexible working basis, even where a position is advertised as full-time, unless there are operational or other objective reasons why it is not possible to do so.

We are a world‑leading research‑intensive university founded in 1965. We are ranked 106th in the world and 8th in the UK.
* Additionally, 92% of our research is rated world‑leading or internationally excellent.**

Find out more about us at

• World University Ranking 2024, Guardian University Guide 2025
• Research Excellence Framework 2021

CLOSING DEADLINE:
Sunday 15th March 2026 at 11:55pm (UK Time)

To apply, please click “Apply” below and…