Group ICT Data Analyst

Middlesbrough
3 months ago
Applications closed

Related Jobs

View all jobs

Performance and Data Analyst (SEND)

Data Quality & Systems Manager

Group Head of Data - Enterprise Data Strategy - Microsoft Fabric - Permanent - London

Data Engineer

Insurance Business Data Analyst

Data Analyst

We are the leading provider of infrastructure services.
At Altrad, we transform our nation’s critical infrastructure to operate safely and sustainably.
With over 11,000 talented people, we provide the full spectrum of critical engineering and construction services for industries both onshore and offshore.
Role Details:
Group ICT Data Analyst - Middlesbrough
This position is based within the ICT Department.
This role involves working closely with the SharePoint Development Team Leader and analysing business processes to help create application solutions using a range of tools including but not limited to Microsoft SharePoint, Nintex Workflow, Power Automate, PowerApps and Power Bi.
The role would suit someone creative, willing to learn and with an interest in starting their career working for a large multi-national organisation in a pivotal role.
Key Responsibilities:

  • Liaise effectively with all members of the ICT team.
  • Build excellent working relationships with people at all levels within the Business to maximise efficiencies in their use of ICT Applications.
  • Assist in the creation of solutions within the SharePoint Environment
  • Analyse, document and streamline business processes to propose more adaptive solutions for business areas.
  • Translate business requirements into functional specifications, formal procedures, test plans and user guides as required.
  • Write technical documents for any changes and enhancements
  • Liaise with internal and external customers/parties to resolve cases to the satisfaction of Business in a timely manner.
  • Maintenance of bespoke applications (forms & workflows) using off-the-shelf tools within SharePoint (Nintex Workflow)
  • Maintain confidentiality with sensitive data/information
  • Build and support Power BI reports
  • Build and support Power Automate workflows
  • Build and support PowerApps
    Key Requirements:
  • Good knowledge required of Microsoft applications such as Outlook, Excel, Word
  • Excellent analytical and problem-solving skills
  • Willingness to learn
  • Good all-round attitude to working with others
  • Ability to multi-task
  • Ability to adhere to best practice/process/policy
  • Excellent written and verbal communication skills, including an ability to explain technical issues in a clear and concise manner to non-technically minded users
  • Ability to work with global, cross functional teams.
    Why Join Us?
  • Work on high-impact projects within a leading organisation at the forefront of the industry.
  • Competitive salary and benefits package.
  • Opportunities for career growth and professional development.
  • Collaborative and dynamic work environment with a focus on innovation and excellence.
    Altrad Babcock is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We make hiring decisions based on your experience, skills, and passion for making a difference. Everyone is welcome to apply.
    If you wish to be considered please apply using the link and start your journey with Altrad

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.