Helpdesk and Performance Manager

Foxwist Green

1 year ago

Applications closed

Helpdesk and Performance Manager
£40,000 - £50,000p/a + £5,000 p/a car allowance
Northwich – CW8
Hybrid working – 3 days in the office, 2 from home
We are currently recruiting for a Helpdesk and Performance Manager to work on a large complex TFM contract. Working alongside a dedicated FM team, you will run a helpdesk/finance admin team of 6 who schedule all PPM and Reactive works across the contract. As well as ensuring this runs smoothly, a large part of the role will be working alongside the Account Manager and helping to monitor the overall performance of the contract, running reports and analysing KPI data. You will also help keep the sites compliant, ensuring penalties are actively avoided and financial targets are met to ensure professional services are always delivered to the client.

Duties of the role

Performance Reporting - Support the Account Manager by producing monthly deduction, service and performance reports, daily updates and weekly dashboards and other reports as required.
Performance Management: Monitor performance of contract daily including SLA performance, chasing work down, processing KPI contract requirements and service request management. Identify trends and minimise failures by providing advice, feedback and updates to the team in the promotion of best practice in relation to payment mechanism deductions.
Process Improvement: Leading reviews of data collection processes to maintain high-quality reporting. Creating actionable insights from these reports for the operations team
Data Quality: Ensuring accuracy and reliability in all performance data through rigorous checks.
Risk & Benchmarking: Collaborating with senior leaders to manage contract benchmarking, identify risks, and document mitigating factors.
Governance: Supporting governance through meeting documentation and creating action points. Working in line with guidelines for sustainability and Health and Safety
Helpdesk Management: Responsible for the effective management of the helpdesk, ensuring that all information is correct and that the processes are followed by both the helpdesk team, engineers and by customers.
Team Leadership: Manage the helpdesk team, offering coaching support and monitoring quality for a team of operators including objective setting. Ensure that the Helpdesk Team is adequately skilled and that all training requirements are completed along with completing relevant reviews. Establish and maintain good team morale and drive performance.
In exchange for you hard work you will get the following benefits:

Pension scheme
25 days holiday + bank holidays (33 total)
Company care or £5,000 car allowance
Medical and life insurance
Training and development schemes
Robust additional benefits including discounts on gym, shopping schemes, CSR days off, ability to buy holidays, cycle to work scheme etc
Candidate Requirements

PFI Experience is desirable
Understanding of contractual compliance
Strong Excel skills
Experience with running reports
CAFM proficient
Excellent planning and organisation skills
Experience managing a team of Helpdesk in an FM environment

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

Industry Insights

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

Feb 10, 2026

Careers

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.

Feb 3, 2026

Jobs

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.

Jan 23, 2026

Education

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.