Data Validation and Management Specialist
Role details
Job location
Tech stack
Job description
Be a part of the team testing the next generation of electrified propulsion systems for our products.
We are at the forefront of development in hybrid and full electric powertrains, aiming to deliver electrifying performance and peerless refinement.
We are looking for individuals who are excited about our data management and validation and can bring their passion and experience to our growing team.
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 covering.
The person in data validation and management role will be responsible to provide timely, accurate, secured and accessible test data for wider engineering group to enable efficient engineering decisions.
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Data Sources and Data Acquisition
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Data Quality validation
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Data piping
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Data storage
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Data visualisation
To ensure we can develop world class propulsions systems, we need world class test and data management and validation.
The specialist role looks to enable this seeking a person 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.
Requirements
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Strong programming skills (Python preferred; experience with C#, JavaScript or other languages advantageous).
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Experience building software applications, automation workflows, and data-processing tools.
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Proficiency in designing and operating data pipelines, ETL workflows, and data-validation systems.
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Experience with cloud platforms such as AWS, Google Cloud or Azure.
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Data analysis skills including statistical evaluation, uncertainty analysis and measurement variation.
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Ability to influence engineering stakeholders and recommend data-/software-driven decisions.
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Strong written reporting, documentation, and presentation skills.
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Understanding of physical-measurement systems and their digital data behaviour.
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Familiarity with version control (Git), CI/CD pipelines, containerisation (Docker), and modern dev practices.
Education Required
Degree in Engineering, Computing, Mathematics, Natural Sciences or similar.