Integration Analyst/Developer

Bevendean
9 months ago
Applications closed

Related Jobs

View all jobs

Data Analyst or Cloud Developer

Senior Business Data Analyst

DOMO Data Analyst

Data Engineer

(Senior) Forecasting Data Engineer

Senior Data Engineer (AWS, Airflow, Python)

Integration Analyst/Developer

  • Location: Brighton - Moulsecoomb
  • Salary: £40,497 to £48,149 per annum
  • Closing Date: Sunday 04 May 2025
    This is an exciting opportunity to join our friendly and growing Identity and Access team, and to help construct and manage our next generation Identity and Access Management platform.
    You will liaise with technical specialists within Information Services and other departments to continue to improve the data interfaces between systems to ensure the confidentiality, integrity, and availability of university systems and data. You will advise and offer guidance on technical and process issues, and will be actively involved in the specification, design, and implementation of new services.
    You, as Data Analyst, will keep up to date with developments in best practice, standards, and technologies within the sector and beyond. You will provide day-to-day support for existing services.
    We are looking for a confident and thoughtful coder who has experience with PowerShell and/or Python, and who thrives in an environment where they can share and collaborate.
    The successful Data Analyst candidate will have:
  • Extensive experience of coding in Python, PowerShell, or JavaScript.
  • Demonstrable experience of analysing, developing, documenting, testing, supporting, and maintaining IT services, integrations, and processes
  • The ability to work collaboratively within a team
  • The ability to write clear, detailed, and engaging documents, diagrams, reports, and presentations in a timely manner – collating, analysing, and summarising complex data.
    This Data Analyst role is available on a job share arrangement. In return, the University offers a number of benefits, such as a generous annual leave package, including time off over the Christmas period, as well as a generous pension scheme, travel loan and childcare voucher schemes.
    In addition, to the eight Bank Holidays, there are university discretionary days between Christmas and New Year. All leave, including bank holidays and discretionary days.
    Further details:
    The University is committed to creating and maintaining an inclusive environment for all staff regardless of age, disability, family or caring responsibilities, gender identity, marital status, pregnancy or maternity, race, religion or belief (including non-belief), sex and sexual orientation. We embrace equality and diversity in our working, learning, research and teaching environment and are committed to maintaining a supportive and inclusive community. We particularly encourage applicants from Minority Ethnic backgrounds because the University is under-represented by Minority Ethnic staff. For the vast majority of our roles we operate an agile working system with time split between working on campus and at the employee's home. It is the University's expectation that home working will take place within the UK.
    Further information about working for us, as well as the wide range of benefits we offer, can be found in the working with us section of our vacancies page.
    Data Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Education

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.