Senior Data Engineer

Experis
Leeds
2 days ago
Create job alert

Senior Data Engineer (Contract)

Location: UK (Remote / Hybrid)

Contract Type: Contract (Outside IR35)


Role Overview


We are seeking a Senior Data Engineer (Contract) to support the delivery of secure, business-critical data platforms within high-assurance, regulated environments. The role focuses on designing and implementing resilient data pipelines and integration services that enable controlled data sharing across complex, multi-domain systems, while maintaining strong standards of security, governance, and compliance.


The successful contractor will operate at a senior technical level, contributing to platform design, assuring engineering quality, and supporting delivery in environments where data integrity, availability, and access control are essential.


Key Responsibilities


  • Design, build, and maintain secure, scalable data pipelines and integration services
  • Engineer data solutions that support controlled data access across complex domains
  • Develop production-grade code aligned with secure-by-design principles
  • Model complex datasets to support interoperability and governed access
  • Integrate data from diverse sources, including legacy and operational systems
  • Implement fine-grained access controls, data classification, and governance mechanisms
  • Support deployment and operation of data services across cloud, on-premise, and hybrid environments
  • Collaborate with architects, security specialists, and delivery teams
  • Contribute to design reviews and technical decision-making
  • Ensure performance, resilience, and observability of data platforms
  • Produce and maintain clear technical documentation


Required Skills & Experience


  • Extensive experience operating as a Senior Data Engineer on complex, enterprise-scale platforms
  • Strong programming capability in Python
  • Commercial experience with Java and/or Scala
  • Advanced SQL and strong data modelling skills
  • Proven experience designing and operating ETL / ELT pipelines at scale
  • Solid understanding of distributed systems and data platform architecture
  • Experience with at least one major cloud platform (AWS, Azure, or GCP)
  • Experience with containerisation and orchestration (Docker, Kubernetes)
  • Familiarity with CI/CD pipelines and modern DevOps practices


Experience in Regulated Environments


  • Experience delivering data solutions in regulated or high-assurance settings
  • Understanding of security-focused architectures such as least-privilege access
  • Experience implementing data governance, classification, and policy-driven access controls
  • Comfortable operating in environments with formal assurance, audit, and compliance requirements
  • Able to handle sensitive information in line with contractual and organisational standards


Desirable Experience


  • Knowledge of semantic data, knowledge graphs, or graph databases
  • Experience with RDF, SPARQL, or ontology-based data models
  • Familiarity with controlled or cross-domain data sharing patterns
  • Experience with Infrastructure-as-Code (e.g. Terraform, CloudFormation)
  • Exposure to open-source data platforms or frameworks


Contractor Profile


  • Able to deliver independently with minimal supervision
  • Comfortable working within structured delivery frameworks
  • Strong analytical and problem-solving skills
  • Clear communicator with both technical and non-technical stakeholders
  • Pragmatic, delivery-focused, and quality-driven


Additional Information


Due to the nature of the work, candidates must be eligible to pass background and suitability checks as part of the engagement.

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior 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.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

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.