Data Engineer

Manchester
9 months ago
Applications closed

Related Jobs

View all jobs

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

Data Engineer | ML & Computer Vision on AWS

Data Engineer - DataOps

Data Engineer (Data Science)

Data Engineering & Data Science Consultant

Data Science Engineer

We are seeking a diligent and innovative Data Engineer to join our Analytics team, the successful Data Engineer with be able to demonstrate a strong business acumen. The ideal candidate will ideally worked with ETL processes, Snowflake, and Tableau, and will be instrumental in bridging the gap between data engineering and business strategy.

Client Details

We are a global electronics and manufacturing company that operates in 100 countries. Our UK subsidiary is based in Manchester. We are on a journey to further develop our data first approach this role will play a key part in bridging the gap between or data engineering team and the wider business.

Description

The successful Data Engineer will be responsible for but not limited to:

Building robust, scalable data pipelines.
Implement complex, large scale big data projects with a focus on collecting, managing, analysing and visualising large datasets.
Collaborate with Analytics team to improve data models that feed business intelligence tools.
Ensure data architecture will support the requirements of the business.
Liaise with the IT team and data scientists to strive for greater functionality in our data systems.
Establish efficient, automated processes for model development, validation, implementation and documentation.Profile

The successful Data Engineer should have:

Proficiency in Big Data Modelling, ETL and Data warehousing.
Proficient in SQL
Snowflake
Tableau
Understanding of cloud services providers.
Excellent problem-solving abilities and communication skills.
An understanding of Python and Java would be advantageous but not essential.Job Offer

An attractive salary package, ranging approximately between £50,000 - £55,000 per annum.
A vibrant and supportive work culture that values innovation and collaboration.
Hybrid working
Generous holiday leave.
A chance to be part of a growing and dynamic team within the technology and electronics industry.We encourage all qualified candidates to apply and contribute to our culture of excellence in Manchester

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 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.

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.

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.