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

Apply Now

Data Engineer

Uniserve Group
City of London
6 days ago
Create job alert

Uniserve is seeking an experienced Data Engineer to join our team and play a pivotal role in designing, building, and optimising our enterprise data platform using Microsoft Fabric. This is a high-impact role for someone passionate about building scalable, secure, and high-performance data solutions that enable advanced analytics and data-driven decision-making across the organisation.

Key Responsibilities

  • Design and implement scalable data architectures using Microsoft Fabric (Lakehouse, OneLake, Spark, Delta Lake).
  • Build and optimise complex data pipelines across the Medallion Architecture for analytics-ready data.
  • Develop reusable data models, semantic layers, and curated datasets for enterprise-wide use.
  • Write production-grade code in Python, SQL, and Scala, following best practices for modularity, testing, and performance.
  • Implement and enforce data governance, lineage, and metadata standards (Microsoft Purview).
  • Drive adoption of CI/CD, version control, and DevOps practices for data engineering workflows.
  • Monitor and resolve performance bottlenecks in Spark jobs and large-scale queries.
  • Collaborate with architects, analysts, and business leaders to align data solutions with strategic goals.
  • Evaluate and introduce new tools, frameworks, and patterns for scalability and maintainability.
  • Contribute to platform reliability, cost optimisation, and security using architectural best practices.

Skills & Experience

  • Proven experience in data engineering with expertise in Microsoft Fabric or similar cloud platforms.
  • Advanced proficiency in Python, Spark, and Scala for data processing and pipelines.
  • Strong understanding of Medallion Architecture, Delta Lake, and distributed data systems.
  • Experience with Spark performance tuning and optimisation.
  • Solid knowledge of data governance, lineage, and metadata management (Microsoft Purview preferred).
  • Familiarity with CI/CD pipelines, Git, and DevOps practices.
  • Ability to design and implement reusable data models and semantic layers.
  • Excellent problem-solving and troubleshooting skills.
  • Strong communication skills with technical and non-technical stakeholders.
  • Relevant qualifications or certifications (e.g., DP-203, CDMP, DGCP, Masters in a related field) are advantageous.

Benefits:

  • Competitive Salary: We value your skills and commitment.
  • Discretionary Bonus: Because your hard work deserves to be rewarded.
  • Pension Scheme: We've got your future covered.
  • Annual Salary Review: Your growth matters to us.
  • Free Eye Test and up to £69 Vouchers towards Glasses: Taking care of your vision.
  • Interest-Free Company Loan: We're here to support you.
  • Free On-Site Parking: Convenient and hassle-free.
  • Cycle to work scheme
  • Referral Bonus £750: Spread the word and earn some extra cash.
  • Care First Lifestyle Programme: Because your well-being matters.
  • Flu Jabs Annually: Stay healthy, on us!
  • Life Assurance: We've got you covered.
  • Electric Vehicle Charging Points at Work: Embrace sustainable transport.
  • Flexible Career Pathway.
  • Supply Chain Academy Education Courses: Expand your knowledge through our Apprenticeships and Commercial Courses.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

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.