Data Engineer

Zealous Agency
Leeds
2 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

If you’re looking to join a highly skilled team in a major Leeds consultancy that has had some key client wins then this is the role for you. They are a major UK player with an established data team and several new projects to get stuck into.


You’ll be deployed on to a variety of different and engaging projects with the remit to deliver data focussed solutions. You’ll be part of an ever-expanding team that is becoming a key part of the company’s overall offering. They’re cloud-agnostic and always looking for the right tool to bring the right solution.


If you want to solve complex data problems in a close-knit team, then you’re the right person for this role.


Key skills needed

  • SQL, Python
  • Data warehousing, relational databases, BigQuery
  • Any Kubeflow, Dataflow experience
  • Docker
  • Multi-cloud experience, Azure used mainly, AWS and/or GCP desirable
  • Any ML experience
  • Marketing platform API experience

If you want to find out more and review the full JD then get in touch for more details or drop Ben Greensmith a message on LinkedIn.


Seniority level

Mid-Senior level


Employment type

Full-time


Job function

Information Technology


Industries

Software Development, Data Infrastructure and Analytics, and Marketing Services


Referrals increase your chances of interviewing at Zealous Agency by 2x


Get notified about new Data Engineer jobs in Leeds, England, United Kingdom.


#J-18808-Ljbffr

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.

Products

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Advertising machine learning jobs in the UK requires a different approach to most technical hiring. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

New Machine Learning Employers to Watch in 2026: UK and Global Companies Driving ML Innovation

Machine learning (ML) has transitioned from a specialised field into a core business capability. In 2026, organisations across healthcare, finance, robotics, autonomous systems, natural language processing, and analytics are expanding their machine learning teams to build scalable intelligent products and services. For professionals exploring opportunities on www.MachineLearningJobs.co.uk , understanding the companies that are scaling, winning investment, or securing high‑impact contracts is crucial. This article highlights the new and high‑growth machine learning employers to watch in 2026, focusing on UK innovators, international firms with significant UK presence, and global platforms investing in machine learning talent locally.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

🍪 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.