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

Apply Now

Principal Data Engineer

Xcede
London
3 months ago
Applications closed

Related Jobs

View all jobs

Principal Data Engineer/Architect

Principal Data Engineer

Principal Data Engineer

Principal, Data Engineering (Remote)

Principal, Data Engineering (Remote)

Principal Geospatial Data Engineer

Xcede is excited to be partnering with a leading global consultancy to grow their Data Engineering capability across the UK.

They’re hiring a Principal Data Engineering Consultant to join their dynamic, fast-growing Data & Analytics team.

You’ll work on high-impact infrastructure projects, designing and building scalable cloud data solutions that enable clients to unlock real value from their data assets.

Tech you’ll be working with:
• Azure Data Factory, Data Lake, Synapse, Databricks
• SQL, Python, Spark, DAX
• Azure DevOps, CI/CD, Git
• Bonus: MLflow, Kubernetes, Kimball modelling, MLOps

What you’ll do:
• Build & maintain modern cloud-based data pipelines
• Translate business needs into scalable data solutions
• Solve data quality issues and improve infrastructure
• Collaborate with cross-functional teams
• Mentor others and shape team best practices

Why join?
You’ll be part of a forward-thinking team working on some of the most exciting infrastructure projects in the world. Expect great tech, a supportive environment, and serious career growth.

Interested?
Apply via the link or reach out to me – drop me a message here on LinkedIn or email me directly at – happy to chat through the details!

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.

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.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.