Site Services Manager

Hoddesdon
2 months ago
Applications closed

Related Jobs

View all jobs

Arboricultural Project Manager (Highways)

Analytics Governance Analyst

Analytics Governance Technical Analyst

Storesperson / Technician

Global Mobility and Immigration Adviser

Power BI Specialist

Facilities Team Manager
Our client operate the UK’s ONLY flexible multi-temp, shared customer delivery logistics network. They buy, warehouse, pick and distribute products to the nation’s best loved food and drink brands every single day and provide the best experience to our customers.
They are currently recruiting a Facilities Team Manager to Lead the Facilities team at the 2 Hoddesdon sites to ensure first-class maintenance services are delivered. Adhering to legislative requirements and meeting agreed KPI’s & SLA’s across the distribution centre.
This role is 40 hours a week, Monday to Friday however flexibility is required, dependent on the needs of the business. Weekend working and/or public holidays may be required.
Main responsibilities will include, but are not limited to the following:

  • Responsible for the day-to-day management of the 2 sites Facilities services and visiting contractors
  • To ensure all plant, equipment and buildings are well maintained and compliant
  • Ensure all planned maintenance and documentation is completed and up to date
  • Ensure contractors working on site adhere to company procedures and comply with Health & Safety including all permits and authorisations
  • Develop positive relationships with other members of the management team, colleagues, and team members
  • Oversee and manage costs in line with repairs and maintenance budgets
    You will need:
  • Working knowledge of electrical/ mechanical systems such as heating, ventilation, air conditioning, refrigeration
  • Intermediate level of all Microsoft packages
  • Good problem-solving skills
  • Ability to prioritise and be resilient
  • A good understanding of Health & Safety legislation
  • Ability to build effective team relationships, ensuring that team members are committed to site objectives
  • Ability to communicate effectively at all levels
  • Understand the nature of costs and benefits to the company both qualitative and quantitative.
  • Understand Company policies and how to implement and interpret these to gain maximum benefits for the company
  • Willing to be flexible to meet the needs of a seven-day a week operation

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.