National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Data Engineer

The Benchmarking Network
Manchester
20 hours ago
Create job alert

About the Role

We are looking for an experienced Senior Data Engineer with strong technical expertise and innovative mindset to drive our team forward. The primary purpose of the role is to be responsible for designing, building, optimising and maintaining the infrastructure that allows data to flow from various sources to storage systems, supports data storage, processing, and analysis, enables high-quality, secure, and scalable data delivery across the organisation. Data Engineer will be involved in the entire data pipeline from data acquisition to data extraction, ensuring that the data is accurate, reliable, and accessible, and fit-for-purpose for business intelligence, analytics, and data science functions. Data Engineer will be collaborating with cross-functional teams to support the delivery of impactful analytics work for our clients.


Job Opportunity

  1. Designing, building and maintaining data pipelines.
  2. Building and maintaining data warehouses.
  3. Data cleansing and transformation.
  4. Developing and maintaining ETL processes (ELT = extract, transform, load) to extract, transform, and load data from various sources into data warehouses.
  5. Validating charts and reports created by systems built in-house. Creating validation tools.
  6. Developing and maintaining data models, data tools.
  7. Monitoring and optimising the performance of data pipelines, data storage and processes, identifying and resolving bottlenecks to ensure efficient data processing and retrieval.
  8. Ability to integrate data from multiple sources, including databases, APIs, websites, and flat files for efficient data processing.
  9. Selecting and integrating appropriate tools and technologies
  10. Troubleshooting and resolving data-related issues.
  11. Architect scalable data solutions to support advanced analytics, machine learning, and real-time processing needs.
  12. Design and implement data governance frameworks, including metadata management, lineage tracking, and cataloging.
  13. Ensuring data quality and reliability; ensuring data security and compliance, including GDPR.
  14. Document data engineering standards, design decisions, and infrastructure setup for operational transparency.
  15. Collaborating with other teams to ensure data availability.
  16. Collaborate with data scientists and analysts to ensure data availability for experimentation, model training, and deployment.
  17. Defining and delivering clear data engineering work packages and deliverables.
  18. Supporting the implementation of new infrastructure to improve the quality and efficiency of projects delivery.
  19. Identify opportunities for innovation, improved productivity, efficiency, and quality.
  20. Evaluate and prototype new tools or technologies, recommending enhancements to the existing data stack.


Essential Skills

  • At least 3 years industry experience.
  • Experience in R programming language.
  • Experience in Python programming language.
  • Knowledge and proficiency in working with database systems (SQL/PostgreSQL) and writing performant SQL queries.
  • Experience in designing, building and maintaining data pipelines.
  • Experience with data warehousing and data lakes.
  • Experience in developing and maintaining ETL processes.
  • Experience in developing data integration tools.
  • Experience in data manipulation, data analysis, data modelling.
  • Experience with cloud platforms (AWS, Azure, etc.)
  • Experience in designing scalable, secure, and cost-efficient data architectures aligned with business needs.
  • Proficiency in optimising database queries, pipelines, and storage for speed, scalability, and cost-efficiency.
  • Skilled in using Git.
  • Strong track record of problem-solving ability and troubleshooting skills.
  • Excellent IT skills including fluency with all Microsoft packages, particularly Excel, Word, PowerPoint, PowerBi.
  • Evidence of excellent communication and interpersonal skills. Clearly communicate technical concepts to both technical and non-technical audiences.
  • Adaptability and willingness to learn new technologies.


About Company

We are the official research support team for the NHS Benchmarking Network, working with over 300 healthcare organisations across the UK to identify opportunities for service development and quality improvement.

We also serve as the primary source of benchmarking data for the NHS England Workforce, Training and Education team, providing in-depth analysis across national mental health services. Our unique and comprehensive datasets support strategic decision-making and resource allocation across the UK healthcare system.

In addition, we are proud to facilitate two major national audits: the National Audit for Care at the End of Life (NACEL) and the Cardiovascular Disease Prevention Audit (CVDPREVENT).


Benefits

  • Annual bonus scheme (subject to personal and business performance)
  • 25 days holiday increasing to 28 after 18 months service, plus statutory bank holidays
  • Flexible 8-hour shift around 6 core working hours
  • Contributory pension
  • Wellbeing programme, including EAP
  • Life Assurance

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

National AI Awards 2025

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.

How to Get a Better Machine Learning Job After a Lay-Off or Redundancy

Redundancy in machine learning can feel especially frustrating when your role was technically advanced, strategically important, or AI-facing. But the UK still has strong demand for machine learning professionals across fintech, healthtech, retail, cybersecurity, autonomous systems, and generative AI. Whether you're a research-oriented ML engineer, production-focused MLOps developer, or applied scientist, this guide is designed to help you bounce back from redundancy and find a better opportunity that suits your goals.

Machine Learning Jobs Salary Calculator 2025: Figure Out Your True Worth in Seconds

Why last year’s pay survey is useless for UK ML professionals today Ask a Machine Learning Engineer wrangling transformer checkpoints, an MLOps Lead firefighting drift alarms, or a Research Scientist training diffusion models at 3 a.m.: “Am I earning what I deserve?” The honest answer changes monthly. A single OpenAI model drop doubles GPU demand, healthcare regulators release fresh explainability guidance, & a fintech unicorn pays six figures for vector‑search expertise. Each shock nudges salary bands. Any PDF salary guide printed in 2024 now looks like an outdated Jupyter notebook—missing the gen‑AI tsunami, the surge in edge inference, & the UK’s new Responsible‑AI framework. To give ML professionals an accurate benchmark, MachineLearningJobs.co.uk distilled a transparent, three‑factor formula that estimates a realistic 2025 salary in under a minute. Feed in your discipline, UK region, & seniority; you’ll receive a defensible figure—no stale averages, no guesswork. This article unpacks the formula, highlights the forces driving ML pay skyward, & offers five practical moves to boost your value inside the next ninety days.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.