IT Support Engineer/MS Azure/Office365/Cloud/AWS/SC Cleared

Exeter
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer (Automation)

Senior Data Engineer - (Python & SQL)

AWS Data Engineer

Data Engineer (AWS)

Junior Data Engineer

Data Engineer - (Python, SQL, Machine Learning) - Robotics

IT Support Engineer

Location: Exeter (with flexible remote working)
Salary: £50,000 - £60,000 per annum
Benefits: Company Healthcare, Workplace Pension
Security Clearance: UKSV SC Clearance required (or ability to obtain)
Employment Type: Permanent

Shape the future of secure IT services.

A leading provider of secure managed services to the Defence and Government sectors is seeking an experienced IT Support Engineer to join its dynamic and growing technical team.

Operating at the highest standards, this role supports a range of critical systems and cutting-edge technologies in an environment where innovation, security, and service excellence are paramount.

The Opportunity

As a Senior Support Engineer, you'll design, implement, maintain, and support IT infrastructure solutions for high-security environments. You'll apply your technical expertise, problem-solving abilities, and communication skills to deliver robust and resilient systems to an organisation that values technical leadership and innovation.

Your Core Skills Should Include:

Configuration and administration of at least four of the following:

Microsoft 365 / Azure / Intune
VMware / vSphere / VDI Virtualisation
Windows Server / Microsoft SQL Server
Linux Server Administration
Cisco / HP Networking Equipment
Fortinet / Cisco FTD Firewalls
Storage Area Networks
AWS PlatformsAdditional Skills That Will Make You Stand Out:

Documentation, policy, and process creation
Windows client support
Infrastructure or policy as code (Terraform, PowerShell, Ansible)
Software-defined networking
DevOps practices and CI/CD pipelines
Service desk software customisation
Web administration/developmentCertifications such as CISSP, CCNA/CCNP, M365/Azure Cyber Security, or AWS architecture qualifications are highly desirable.

Work Environment

40 hours per week (flexible start/finish times between 08:00 and 17:00)
Office base: Exeter, with flexibility for remote working
High-trust, security-sensitive environment requiring sole UK nationality and ability to gain or hold UK MOD Security Clearance (SC)This is a unique opportunity to apply your skills to projects that truly matter.
If you are driven by technical excellence and want to work at the cutting edge of secure IT solutions, we want to hear from you.

Apply today and make a real impact.

People Source Consulting Ltd is acting as an Employment Agency in relation to this vacancy. People Source specialise in technology recruitment across niche markets including Information Technology, Digital TV, Digital Marketing, Project and Programme Management, SAP, Digital and Consumer Electronics, Air Traffic Management, Management Consultancy, Business Intelligence, Manufacturing, Telecoms, Public Sector, Healthcare, Finance and Oil & Gas

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 Engineering Tools Do You Need to Know to Get a Data Engineering Job?

If you’re aiming for a career in data engineering, it can feel like you’re staring at a never-ending list of tools and technologies — SQL, Python, Spark, Kafka, Airflow, dbt, Snowflake, Redshift, Terraform, Kubernetes, and the list goes on. Scroll job boards and LinkedIn, and it’s easy to conclude that unless you have experience with every modern tool in the data stack, you won’t even get a callback. Here’s the honest truth most data engineering hiring managers will quietly agree with: 👉 They don’t hire you because you know every tool — they hire you because you can solve real data problems with the tools you know. Tools matter. But only in service of outcomes. Jobs are won by candidates who know why a technology is used, when to use it, and how to explain their decisions. So how many data engineering tools do you actually need to know to get a job? For most job seekers, the answer is far fewer than you think — but you do need them in the right combination and order. This article breaks down what employers really expect, which tools are core, which are role-specific, and how to focus your learning so you look capable and employable rather than overwhelmed.

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

If you’re applying for data engineering jobs in the UK, the first thing to understand is this: Hiring managers don’t read every word of your CV. They scan it. They look for signals of relevance, credibility, delivery and collaboration — and if they don’t see the right signals quickly, your application may never get a second look. In data engineering, hiring managers are especially focused on whether you can build and operate reliable, scalable data systems, handle real-world data challenges and work effectively with analytics, BI, data science and engineering teams. This guide breaks down exactly what they look at first in your application — and how to shape your CV, portfolio and cover letter so you stand out.

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

Data engineering has quietly become one of the most critical roles in the modern technology stack. While data science and AI often receive the spotlight, data engineers are the professionals who design, build and maintain the systems that make data usable at scale. Across the UK, demand for data engineers continues to rise. Organisations in finance, retail, healthcare, government, media and technology all report difficulty hiring candidates with the right skills. Salaries remain strong, and experienced professionals are in short supply. Yet despite this demand, many graduates with degrees in computer science, data science or related disciplines struggle to secure data engineering roles. The reason is not academic ability. It is a persistent skills gap between university education and real-world data engineering work. This article explores that gap in depth: what universities teach well, what they consistently miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data engineering.