Lead Data Engineer

Burns Sheehan
Brighton, England
10 months ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Canada Life London, United Kingdom
£70,000 – £100,000 pa Hybrid

Senior Data Scientist

Adria Solutions Manchester, United Kingdom
Permanent

Data Scientist / AI Engineer

Searchability NS&D Cheltenham, United Kingdom
£45,000 – £95,000 pa On-site Clearance Required

Data Engineer, Strategic Account Services

Amazon London, United Kingdom
Permanent

Senior Data Engineer - Microsoft Fabric

Harvey Nash London, United Kingdom
£80,000 – £90,000 pa Hybrid

Lead Data Scientist

Technify Talent Limited United Kingdom
£80,000 – £90,000 pa Remote
Posted
26 Jun 2025 (10 months ago)

Lead Data Engineer

£75,000-£85,000

️ AWS, Python, SQL, Airflow

Brighton, hybrid working

Analyse customer behaviour using AI & ML

We are partnered with a private equity backed company who provide an AI-powered, guided selling platform that helps businesses improve online sales and customer experience.

They are looking for a Lead Data Engineer to lead a small team in building a key part of their data infrastructure.

The role...

This role blends people management, individual contribution, and technology leadership.

What you'll be doing...

  • Individual Contribution: You will take ownership of project briefs and design robust architectural plans. You will also champion the importance of thorough testing and ensure alignment with stakeholder expectations throughout the development process.
  • People Management: You will lead and mentor a small team of Data Engineers, fostering a high-performance culture by guiding their professional growth and ensuring effective communication within the team and with stakeholders.
  • Technology Leadership: You will guide strategic decision-making regarding technology and architecture, ensuring solutions are scalable, cost-effective, and flexible enough to meet diverse customer needs.

What they are looking for...

  • Strong commercial experience in a Senior Data Engineering role.
  • Comfortable owning and delivering technical projects end-to-end.
  • Strong in Python, SQL, and cloud platforms (AWS or comparable).
  • Experience with Airflow, Snowflake, Docker (or similar).
  • Familiarity with coaching and mentoring more junior engineers, leading 1-1s and check ins.

Wider tech stack: AWS, Python, Airflow, Fivetran, Snowflake, Looker, Docker.

What's in it for you...

  • Medicash healthcare scheme (reclaim costs for dental, physiotherapy, osteopathy and optical care)
  • Life Insurance scheme
  • 25 days holiday + bank holidays + your birthday off (rising to 28 after 3 consecutive years with the business & 30 after 5 years)
  • Employee Assistance Programme (confidential counselling)
  • Enhanced parental leave and pay

If you are interested in finding out more, please apply or contact me directly!

Lead Data Engineer

£75,000-£85,000

️ AWS, Python, SQL, Airflow

Brighton, hybrid working

Analyse customer behaviour using AI & ML

Burns Sheehan Ltd will consider applications based only on skills and ability and will not discriminate on any grounds.


#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.

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.

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.

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.