Head of IT & Digital Services - Office Based Role Trafford Park MCR

Eccles
8 months ago
Applications closed

Related Jobs

View all jobs

Head of IT and Business Intelligence

Data Engineer (18 Months FTC)

Data Engineer (18 Months FTC)

Data Architect

Head of Data Analytics

Head of Data Science

Reliance High-Tech is the UK's largest independent integrator/installer of security solutions. We are trusted by leading brands and organisations to protect their people, assets and reputations through innovative technology and specialist expertise.
Unique in the industry, Reliance High-Tech combines the capability and footprint of a large organisation, with the agility and customer focus of an independent business.
We operate at the top end, for the most discerning clients, in the most demanding and complex environments with the highest stakes, and always with integrity and customer focus.
This is an ideal step-up role for a technically strong IT professional ready to move into formal leadership. As Head of IT & Digital Services, you'll lead three growing teams—IT, Software Development, and Information Security—while remaining hands-on in delivery, automation, and systems improvement. This hybrid “doer-manager” role offers the opportunity to drive internal change, enhance service delivery, and shape a high-performing tech function aligned with business goals.
Your Responsibilities

  • Drive improvements across internal IT systems, infrastructure, and support processes
  • Contribute hands-on to technology projects, especially in automation and service optimisation
  • Shape and grow the internal IT, InfoSec, and software development capabilities
  • Work closely with stakeholders to identify inefficiencies and deliver practical, tech-enabled solutions
  • Support the development and delivery of internal business intelligence and reporting tools
  • Maintain and improve information security practices in line with business requirements
  • Champion a culture of learning, collaboration, and continuous improvement
    Your Competencies
  • Proven experience in a senior IT or technical role (e.g. infrastructure, dev, automation)
  • Strong technical capability with hands-on experience in systems support or solution delivery
  • Experience working with internal IT systems, development projects, or business automation
  • Familiarity with cloud platforms (e.g. Azure, AWS) and modern IT practices
  • Excellent interpersonal and communication skills, with the ability to lead by example
  • Clear problem-solving mindset with a practical, delivery-oriented approach
    Your Profile
    The ideal candidate will be hands-on, proactive, and focused on delivering results, with a strong commitment to continuous improvement without needing close direction. They should be comfortable balancing day-to-day operational tasks with broader leadership responsibilities. A positive and collaborative approach is essential, along with the ability to build strong relationships across teams.
    To express an interest in this role please send your CV and a covering
    All job candidates will be screened to BS7858 standards to meet Reliance High-Tech's vetting standards. You must provide your location on your CV and or Covering letter - this is mandatory.
    If you have not heard from us within two weeks of submitting your application, unfortunately, it means your application has not been successful at this time.
    We will, however, keep your details on file, and if your skills and experience align with future opportunities, we may contact you directly

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.