Assistant Finance Manager (22.5 hours)

Deeside
9 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Junior Data Governance Analyst | £35,000 + Bonus & 10% Pension

Data Engineer - Contract - 9+ Months

IT Data Engineer

Job Title: Assistant Finance Manager
Location: Deeside, near Chester
Contract Details: 12 month FTC, Part-time (22.5 hours/week)

Responsibilities:

  • Ensure timely receipt and update of all performance and financial inputs in the organisation's systems.
  • Monitor and manage depot fuel usage, fleet costs, and mileage records.
  • Oversee 3rd Party storage stock levels, transport costs, and inter-depot transfer expenses.
  • Support the production of weekly and period cost reporting for Supply Chain.
  • Conduct depot balance sheet reviews and provide insights to the Finance Manager.

    Key Accountabilities:

  • Understand the data received from 3rd Party Logistics (3PL) providers, ensuring it's timely and accurately filed.
  • Monitor provider performance to guarantee accurate and timely data delivery.
  • Maintain organisation of files and ensure updates in financial and performance monitoring documents.
  • Update weekly financial performance data and assist the Finance Manager in generating cost reports.
  • Validate and report on 3rd Party storage and transport costs, ensuring accurate records.
  • Track depot vehicle fleet numbers and develop insightful reporting to challenge usage.
  • Aid in producing period accounts, budgets, and forecasts.
  • Participate in reviews of Depot charges and balance sheets, including onsite visits.
  • Support the Finance Manager in maintaining proper records for strategic projects.
  • Provide general support and cover within the Supply Chain Commercial function.

    Qualifications/Technical Skills:

  • Advanced Excel skills.
  • Familiarity with databases and SQL is an advantage.
  • Experience with SAP or similar accounting software.
  • Exceptional attention to detail and an enquiring mindset.
  • Ability to meet deadlines confidently while communicating with internal and external stakeholders.
  • Experience in logistics or general accounting is a plus.

    What We Offer:
    Join our client and make a significant impact on your career! In return, they'll provide:

  • 15% discount in retail stores.
  • 30% discount at Club Individual Restaurants.
  • 33 days holiday (including bank holidays).
  • Pension scheme (NEST).
  • Free onsite parking and electric car charging ports.
  • Subsidised staff restaurant and Costa Coffee.
  • Christmas vouchers and a refer-a-friend scheme.
  • Christmas savings scheme and discounted dry cleaning.
  • Long service awards to celebrate your journey with us.

    If you're ready to make a difference and grow in a dynamic environment, we want to hear from you! Apply now and take the next step in your career with us.

    Adecco acts as an employment agency for permanent recruitment and an employment business for the supply of temporary workers. The Adecco Group UK & Ireland is an Equal Opportunities Employer.

    By applying for this role your details will be submitted to Adecco. Our Candidate Privacy Information Statement explaining how we will use your information is available on our website

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.