Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Engineer

Harnham
Nottingham
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

DATA ENGINEER

£75,000-£80,000 + BENEFITS

PRIMARILY REMOTE

A leading digital platform in the property industry is seeking a proactive Senior Data Engineer to join their innovative team.

THE COMPANY:

This is a well-established brand driven by an ambitious vision. They are currently investing in their data team, and are looking to expand and enhance its services.

THE ROLE:

A Senior Data Engineer will need to:

  • Work closely with stakeholders across the business
  • Oversee end to end processes, ensuring scalability of pipelines
  • Implementing best practices in data governance and infrastructure set up

YOUR SKILLS AND EXPERIENCE:

A successful Senior Data Engineer will have the following skills and experience:

  • Ability and experience interacting with key stakeholders
  • Cloud experience - Azure preferred
  • Containerisation experience - Kubernetes preferred
  • Prior experience with Pyspark
  • Understanding of IaC/Terraform

THE BENEFITS:

You will receive a salary, dependent on experience. Salary is up to £80,000 On top of the salary there are some fantastic extra benefits.

HOW TO APPLY

Please register your interest by sending your CV to Molly Bird via the apply link on this page.

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.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.