Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Data Management and Validation Engineer

Coventry
1 month ago
Applications closed

Related Jobs

View all jobs

Quantitative Research - Data Product Owner - Credit - Executive Director

Quantitative Risk & Data Analyst

Data Analyst

Data Analyst

Data Analyst

Data Analyst

Our premium brand Automotive client is currently recruiting for the following role:

Data Management and Validation Engineer - £28/hr (Inside IR35) - Coventry (hybrid potential) - 9 Months (potential for yearly renewal)

The Opportunity
Be a part of the team testing the next generation of electrified propulsion systems for luxury automotive products. Our client is at the forefront of development in hybrid and full electric powertrains, aiming to deliver electrifying performance and peerless refinement. This role will work across Electric machine, Electric Drive Unit (EDU), Inverter, Cell, Battery, Power in loop (PiL) and Vehicle in Loop (ViL) test beds. The person in this data validation and management role will be responsible in providing timely, accurate, secured and accessible test data for wider engineering group to enable efficient engineering decisions.

  • Data Sources and Data Acquisition
  • Data Quality validation
  • Data piping
  • Data storage
  • Data visualisation

    The specialist role requires an individual with knowledge of different testing environments data management and validation. The role will require you to work cross functionally to deploy a common approach to data piping, data validation tools as well to build a federated data platform. You will be working towards becoming the Subject Matter Expert for data management and validation and deliver a training package to develop others in order to improve the data quality produced by the team.

    Key Accountabilities and Responsibilities
  • Be responsible in data sources and data acquisition, data quality validation, data pipeline, data storage and data visualisation for physical test environment.
  • Delivering data quality reviews to support programme targets and prove out chosen technologies.
  • Develop calculations, parameterisation, regulations and process of in-house data tool development.
  • Be responsible for confirming the facility is performing in repeatable and reproducible measurements compliant to regulations.
  • Carry out correlation exercises between test facilities and test beds across test operation.
  • Ensure continuous improvement of measurement quality by reviewing the measurement equipment, systems and methods used by providing data.
  • Perform calculation and evaluation of test results, particularly of results from internal correlation measurements, and initiate corrective measures as required.
  • Cooperate in projects for improving test bed consistency and repeatability (together with experts from internal departments and the Instrumentation & Test Systems business unit).
  • Working closely with the subject matter expert for Data Quality ensuring that the team KPI's for Data Quality are met
  • Recommend and justify process and other improvements to enable improved quality of data
  • Research, communicate and implement best practice data quality methods and improve test field efficiency.
  • Investigate best ways of working to make full use of equipment capability to improve data quality
  • To continually encourage a growth mind-set across the team
  • Coaching and facilitating in best technical practice, knowledge, methods in data validation and management for apprentice, new starter and existing team member development.
  • Undertake any other work as directed by their line manager in connection with their job as may be requested

    Knowledge, Skills and Experience
  • Educated to degree level in a natural science, mathematical or engineering or computing discipline.
  • Designing applications in different programming languages (preferable Python)
  • Build data systems & pipelines, data validation and management in cloud platforms (AWS, Google Cloud).
  • Data analysis skills, including hypothesis testing, uncertainty analysis, and process variation.
  • Ability to work closely with engineering stakeholders influence analysis techniques to inform engineering decisions.
  • Develop Key Performance Indicator (KPI) and ability to graphical data presentation.
  • Technical / theoretical understanding of physical measurement equipment
  • Ability to deliver written reports and technical presentations.
    Desirable
  • Academic thesis or capstone project in formal field of study.
  • Six Sigma Green Belt
  • Technical knowledge of process, calculation and measurement techniques demanded by both engineering and legislative requirements.
  • Experience in measurement science.
  • Quantitative understanding of equipment measurement sensitivity

    Additional information:
    This role is on a contract basis and is Inside IR35.
    The services advertised by Premea Limited for this vacancy are those of an Employment Business.
    Premea is a specialist IT & Engineering recruitment consultancy representing clients in the UK and internationally within the Automotive, Motorsport and Aerospace sectors

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.

Seasonal Hiring Peaks for Data Science Jobs: The Best Months to Apply & Why

The UK's data science sector has matured into one of Europe's most intellectually rewarding and financially attractive technology markets, with roles spanning from junior data analysts to principal data scientists and heads of artificial intelligence. With data science positions commanding salaries from £30,000 for graduate data analysts to £140,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this intellectually stimulating and rapidly evolving field. Unlike traditional analytical roles, data science hiring follows distinct patterns influenced by business intelligence cycles, research funding schedules, and machine learning project timelines. The sector's unique combination of mathematical rigour, business impact requirements, and cutting-edge technology adoption creates predictable hiring windows that strategic professionals can leverage to advance their careers in extracting insights from tomorrow's data. This comprehensive guide explores the optimal timing for data science job applications in the UK, examining how enterprise analytics strategies, academic research cycles, and artificial intelligence initiatives influence recruitment patterns, and why strategic timing can determine whether you join a pioneering AI research team or miss the opportunity to develop the next generation of intelligent systems.

Pre-Employment Checks for Data Science Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in data science reflects the discipline's unique position at the intersection of statistical analysis, machine learning innovation, and strategic business intelligence. Data scientists often have privileged access to comprehensive datasets, proprietary algorithms, and business-critical insights that form the foundation of organisational strategy and competitive positioning. The data science industry operates within complex regulatory frameworks spanning GDPR, sector-specific data protection requirements, and emerging AI governance regulations. Data scientists must demonstrate not only technical competence in statistical modelling and machine learning but also deep understanding of research ethics, data privacy principles, and the societal implications of algorithmic decision-making. Modern data science roles frequently involve analysing personally identifiable information, financial data, healthcare records, and sensitive business intelligence across multiple jurisdictions and regulatory frameworks simultaneously. The combination of analytical privilege, predictive capabilities, and strategic influence makes thorough candidate verification essential for maintaining compliance, security, and public trust in data-driven insights and automated systems.

Why Now Is the Perfect Time to Launch Your Career in Data Science: The UK's Analytics Revolution

The United Kingdom stands at the forefront of a data science revolution that's reshaping how businesses make decisions, governments craft policies, and society tackles its greatest challenges. From the machine learning algorithms powering London's fintech innovation to the predictive models guiding Manchester's smart city initiatives, Britain's transformation into a data-driven economy has created an unprecedented demand for skilled data scientists that far outstrips the available talent. If you've been contemplating a career transition or seeking to position yourself at the cutting edge of the digital economy, data science represents one of the most intellectually stimulating, financially rewarding, and socially impactful career paths available today. The convergence of big data maturation, artificial intelligence mainstream adoption, business intelligence evolution, and cross-industry digital transformation has created the perfect conditions for data science career success.