Data Management and Validation Engineer
Data Management and Validation Engineer

Data Management and Validation Engineer

Coventry Full-Time No home office possible
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At a Glance

  • Tasks: Manage and validate data for cutting-edge electric vehicle testing.
  • Company: Join a leading luxury automotive brand revolutionising electrified propulsion systems.
  • Benefits: Enjoy hybrid work options and competitive pay of £28/hr.
  • Why this job: Be part of an innovative team shaping the future of sustainable automotive technology.
  • Qualifications: Knowledge of data management in testing environments is essential.
  • Other info: Potential for yearly renewal and opportunities for professional development.

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

Data Management and Validation Engineer employer: Premea

Join a leading automotive brand in Coventry, where innovation meets excellence. As a Data Management and Validation Engineer, you'll thrive in a collaborative work culture that prioritises employee growth and development, offering unique opportunities to work on cutting-edge electrified propulsion systems. With hybrid working options and a commitment to delivering high-quality data solutions, this role not only promises meaningful contributions but also a rewarding career path in the dynamic automotive industry.
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Contact Detail:

Premea Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Management and Validation Engineer

✨Tip Number 1

Familiarise yourself with the latest trends in data management and validation, especially within the automotive sector. Understanding the specific technologies and methodologies used in electric propulsion systems will give you an edge during discussions.

✨Tip Number 2

Network with professionals in the automotive industry, particularly those involved in data management and validation. Attend relevant webinars or industry events to make connections that could lead to valuable insights and potential referrals.

✨Tip Number 3

Prepare to discuss your experience with data quality validation and data visualisation tools. Be ready to share specific examples of how you've successfully managed and validated data in previous roles, as this will demonstrate your expertise.

✨Tip Number 4

Showcase your ability to work cross-functionally by highlighting any past experiences where you've collaborated with different teams. This is crucial for the role, so emphasising your teamwork skills can set you apart from other candidates.

We think you need these skills to ace Data Management and Validation Engineer

Data Management
Data Validation
Data Quality Assurance
Data Acquisition Techniques
Data Piping
Data Storage Solutions
Data Visualisation Tools
Knowledge of Testing Environments
Cross-Functional Collaboration
Subject Matter Expertise
Training and Development Skills
Analytical Skills
Attention to Detail
Problem-Solving Skills
Technical Aptitude

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience in data management and validation. Focus on specific projects or roles where you've worked with data quality validation, data acquisition, and visualisation.

Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the automotive industry. Mention your understanding of electrified propulsion systems and how your skills align with the responsibilities outlined in the job description.

Showcase Technical Skills: Clearly list any technical skills related to data piping, storage, and validation tools. If you have experience with specific software or methodologies used in data management, be sure to include those details.

Highlight Cross-Functional Experience: Since the role requires working cross-functionally, provide examples of past experiences where you've collaborated with different teams. This will demonstrate your ability to communicate and work effectively in a team environment.

How to prepare for a job interview at Premea

✨Understand the Role

Make sure you thoroughly understand the responsibilities of a Data Management and Validation Engineer. Familiarise yourself with terms like data piping, data validation tools, and the specific testing environments mentioned in the job description.

✨Showcase Relevant Experience

Prepare to discuss your previous experience with data management and validation. Highlight any projects where you worked with electric machines, inverters, or battery systems, as this will demonstrate your suitability for the role.

✨Prepare Questions

Have insightful questions ready about the company's approach to data management and the technologies they use. This shows your genuine interest in the role and helps you assess if the company is the right fit for you.

✨Demonstrate Teamwork Skills

Since the role involves cross-functional collaboration, be prepared to share examples of how you've successfully worked in teams. Emphasise your ability to communicate effectively and contribute to a common goal.

Data Management and Validation Engineer
Premea
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