BOM Validation Engineer

Warwick
2 weeks ago
Create job alert

Expleo is a trusted global partner for end-to-end, integrated engineering, quality services, and management consulting. We help businesses harness the power of innovation to drive real progress and deliver future-ready solutions.

We're currently seeking a BOM Validation Engineer to join the Product Information team, supporting the launch phase of vehicle programmes. This role is essential to ensuring data quality, integrity, and delivery - reducing errors and ensuring alignment across engineering and programme functions. This is a contract role based in the Midlands.

As a BOM Validation Engineer , you will be responsible for driving high-quality data validation activities during the launch phase, from First Build through to Job . You will work cross-functionally with Product Information, Engineering, and Programme teams to ensure that no defects are passed to downstream consumers of PI data, such as build and pricing systems.

You will lead BoM validation sessions, manage data quality metrics, and use key tools such as AIMS to identify and track issues. This is a role that demands strong attention to detail, analytical capability, and proactive communication.

Key Responsibilities

  • Lead and coordinate Bill of Materials (BoM) validation activities in line with PI programme milestones.
  • Organise and facilitate engineering review sessions to validate data accuracy and part usage.
  • Raise and manage issues via AIMS or engineering concern systems and track them to resolution.
  • Maintain and distribute daily validation metrics through a master tracker and reporting tools.
  • Host and lead handover meetings, ensuring all raised items are actioned and closed prior to release.

    Skills and Experience
  • Strong project and time management skills, with the ability to work independently.
  • Ability to conduct detailed data analysis, identify issues, and deliver effective resolutions at pace.
  • Confident communicator able to clearly articulate technical challenges across teams.
  • Proficient in Microsoft Excel (including formulas like VLOOKUP) for data validation and tracking.
  • Basic understanding of BoM usage in an automotive context.
  • Familiarity with Product Information systems and processes.
  • Experience with issue tracking tools such as AIMS.
  • Background in data analytics or quality control.
  • Experience managing technical issues during vehicle launch or engineering development phases.
  • Advanced Excel skills (pivot tables, macros, data visualisation) are a plus.

    To apply or learn more, please contact:
    Leanne Eaton
    (url removed)
    (phone number removed)

    All applications will be treated with the highest level of confidentiality

Related Jobs

View all jobs

Virtual Build Planning Lead

Stores Person

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Top 10 Best UK Universities for Data Science Degrees (2025 Guide)

Discover ten of the strongest UK universities for Data Science degrees in 2025. Compare entry requirements, course content, research strength and industry links to choose the right programme for you. Data is the currency of the modern economy, and professionals who can wrangle, model and interpret vast datasets are in demand across every sector—from biotechnology and finance to sport and public policy. UK universities have been at the forefront of statistics, artificial intelligence and large-scale computing for decades, making the country a prime destination for aspiring data scientists. Below, we profile ten institutions whose undergraduate or postgraduate pathways excel in data science. Although league tables vary each year, these universities have a proven record of excellence in teaching, research and industry collaboration.

Veterans in Data Science: A Military‑to‑Civilian Pathway into Analytical Careers

Introduction The UK Government’s National AI Strategy projects that data‑driven innovation could add £630 billion to the economy by 2035. Employers across healthcare, defence, and fintech are scrambling for professionals who can turn raw data into actionable insights. In 2024 alone, job‑tracker Adzuna recorded a 42 % year‑on‑year rise in data‑science vacancies, with average advertised salaries surpassing £65k. For veterans, that talent drought is a golden opportunity. Whether you plotted artillery trajectories, decrypted enemy comms, or managed aircraft engine logs, you have already practised the fundamentals of hypothesis‑driven analysis and statistical rigour. This guide explains how to translate your military experience into civilian data‑science language, leverage Ministry of Defence (MoD) transition programmes, and land a rewarding role building predictive models that solve real‑world problems. Quick Win: Take a peek at our live Junior Data Scientist roles to see who’s hiring this week.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.