Expleo is currently hiring a Data Analyst to support a leading automotive customer based in Warwickshire. This is an exciting opportunity to work at the forefront of software and systems engineering, helping drive data-driven decision-making across complex engineering programmes. Contract (Annual) £33.88 per hour (Inside IR35) The Role As a Data Analyst specialising in Software & Systems Defects, you will play a critical role in ensuring the accuracy, consistency, and usability of defect data across the organisation. You will act as the bridge between: Testing Engineers Defect Resolution Teams Release & Delivery FunctionsWorking with tools such as JIRA and Tableau, you'll analyse complex datasets, resolve data/tooling challenges, and produce clear, actionable insights for stakeholders at all levels. Key Responsibilities Analyse and manage software and systems defect data to ensure integrity and consistency Generate transparent weekly reports for Senior Management Provide data-driven insights to support project planning and delivery Collaborate with engineering stakeholders to ensure aligned and accurate metrics Interpret complex datasets and communicate key insights effectively Monitor defect tickets to identify and correct data quality issues Drive best practice in defect management, coaching teams on data cleanliness and consistency Support continuous improvement of data processes and toolingSkills & Experience Ability to support project planning with data-driven insights. Ability to create transparent weekly Senior-Management Reporting Ability to interact with key engineering stakeholders to ensure metrics are aligned and correct Ability to interpret the data to determine the key messages that should be shared. Ability to ensure data integrity is maintained, by monitoring tickets for common errors Ability to coach other users with the best practice on defect tooling, data consistency and cleanliness Visualisation tool (e.g. Tableau) experience would be beneficial Apply now to be part of an innovative team shaping the future of engineering data analytics