Overview

Coventry Plant, UKLear, a global automotive technology leader in Seating and E-Systems, enables superior in-vehicle experiences for consumers around the world. Our diverse team of talented employees in 39 countries is driven by a commitment to innovation, operational excellence, and sustainability. Lear is Making every drive better by providing the technology for safer, smarter, and more comfortable journeys. Lear, headquartered in Southfield, Michigan, serves every major automaker in the world and ranks #179 on the Fortune 500. Further information about Lear is available at lear.com or follow us on Twitter @LearCorporation.Lear’s Industry 4.0 StrategyAs a global technology leader of automotive Seating and Electrical components operating across over 250 facilities within 37 countries around the world, Lear Corporation is at the forefront of various aspects of technological evolution. Industry 4.0 within Lear Corporation is underpinned through the integration of intelligent digital technologies and analytical systems into manufacturing and industrial processes. Lear Corporation’s industry 4.0 strategy is primarily divided into 2 key operating functions. Firstly, the successful project management and execution of industry 4.0 initiatives into our manufacturing operations. Secondly, the digital analysis and data gleaned from visual management systems ensuring Lear takes informed decisions across its wider business maximizing our operational efficiency whilst upholding the highest quality standards ensuring that Lear’s operational and financial objectives can be achieved.As a Senior data engineer you will be working with colleagues focused on understanding the operational Use Cases and Data scientists using ML models to deliver solutions to support business decisions. As a data engineer you will be responsible for the development of the data pipelines, their security, reliability and efficiency; supporting industry 4.0 projects and the rollout of activities that are identified.Key Responsibilities

Manage the execution of data-focused projects using Lear’s data analytics and application platform as a member of the EUandAF AME team.Participate in multiple projects from conception to root cause analytics and solution deployment.Support the creation of a user toolset to be deployed as a regional standard across Lear for analyzing and presenting data effectively to senior management.Generate large databases from various sources of both structured and unstructured data.Utilize a range of programming languages to transform big data into manageable datasets.Translate technical data into understandable insights, providing recommendations and conclusions to stakeholders.Understand program and product delivery phases, contributing expert analysis across the lifecycle.Work with both new and legacy technologies to integrate separate data feeds and transform them into new scalable datasets.Ensure documentation and procedures align with internal practices (ITPM) and Sarbanes Oxley requirements, continuously improving them.Optimize system performance for all deployed resources.Experience and Qualifications

Required:Bachelor’s degree qualification in Computer Science, Electronics or Systems / Software Engineering.Experience working as part of an integrated data team.Strong business analysis/requirements analysis skills.Business Analysis.Working within an Agile framework.Preferred:5 years’ experience of working within a multinational organization with international, cross functional teams.5 years’ experience of working within data engineering or optimization to support a high volume manufacturing operation.Master’s degree in Computer Science, Systems, or comparable Electronic Discipline.Experience working with data for ML purposes.Key Skills

Expert level of knowledge of data warehousing and/or relational databases.High Level of knowledge of operating with Python and preferably PySpark Platforms.Experience in data mining methods and data toolsExperience with cloud-based data platforms.Knowledge of applying data lineage, transformation and quality analysis activities.Competent to reach into data sources to create new data extraction interfaces.Proven experience developing data pipelines and ETL processes from disparate data sources.As well as an attractive salary we offer

Group Personal Pension with AVIVAHybrid Working (4+1) (non-contractual)Core hours working (non-contractual)25 days annual leaveLife Cover 3 x Basic Salary (Expression of wishes form required)

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