Data Engineer

Synapri
London
1 year ago
Applications closed

Related Jobs

View all jobs

Data Engineer - AI Analytics and EdTech Developments

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

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

Data Engineering & Data Science Consultant

MLOps Data Engineer (GCP)

MLOps Data Engineer (GCP)

Sector:Public Sector / Government / Defence

Job Title:Data Engineer

Type:Contractor

Location:London (Hybrid)

Duration:End FY – 31/03/2025 (initial)

Vetting:SC level security clearance is required



The Data Engineer role’s primary focus will be on developing the PMO’s Excel-based toolkit to enhance the use of data in strategic decision making across the client.

This will consist of providing rapid development and improvement of tools built in Excel and using the Power platform.


To ultimately assist the PMO to provide delivery, reporting and strategic support.


Experience required

EXPERT in Exceland strong with Power Query and wider Power Platforms suite knowledge & Experience

Advanced Data Modelling experience (financial/budget data) using Power Query.

Reviewing current product in use and building better models that will be better fit for purpose.


  • Passionate about Excel and data with a proven track record of delivering high-quality Excel-based solutions.
  • Extensively experienced in developing, managing, and optimising Excel-based solutions to support various business functions, has a strong understanding of Excel's advanced features and capabilities, and be able to translate requirements into effective Excel solutions.
  • An expert in using Excel’s advanced features including formulas, macros, VBA and Power Query, and familiar with Power Pivot, Power Automate, Power BI Desktop and Power BI Service.
  • Able to work with various data sources, including databases, Excel, SharePoint, APIs, and web services.
  • Meticulous in their approach to data preparation, data cleansing, and report design to ensure data accuracy and quality and the ability to document and present data visualisation solutions clearly.
  • Familiar with data visualisation and the ability to think creatively and innovatively to design and create visually appealing and insightful custom report, dashboard and unique data presentation solutions.
  • Proactive with a “can do” problem-solving approach to address data-related challenges and the ability to adapt to changing data requirements and business priorities.
  • Able to work independently, but also has strong collaboration skills to work closely with business analysts, data engineers, and other team members in multidisciplinary projects.

Professionally qualified in computer science, Information Technology, Data Science or a related field.

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.

Careers

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

Jobs

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

Education

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

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.