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- Tasks: Develop data pipelines and support industry 4.0 projects with cutting-edge technology.
- Company: Join Lear, a global leader in automotive technology with a commitment to innovation.
- Benefits: Competitive salary, diverse team, and opportunities for professional growth.
- Why this job: Make an impact by transforming big data into actionable insights for major automakers.
- Qualifications: Master's degree in Computer Science or related field; experience in data engineering required.
- Other info: Dynamic work environment with a focus on sustainability and operational excellence.
The predicted salary is between 36000 - 60000 £ per year.
As a 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.
Responsibilities
- Manage the execution of data-focused projects using Lear\’s data analytics and application platform as a member of the EU&AF 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.
Qualifications
- Master\’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.
- 2-5 years\’ experience of working within data engineering or optimization to support a high volume manufacturing operation.
- 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 tools
- Experience 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.
- Proficiency in English, spoken and written
Lear, a global automotive technology leader in Seating and E-Systems, enables superior in-vehicle experiences for consumers around the world. Our diverse team of more than 165,000 talented employees in 37 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 #186 on the Fortune 500. Further information about Lear is available at lear.com, or follow us on Twitter @LearCorporation
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Foundry Data Analyst employer: Lear Corporation
Contact Detail:
Lear Corporation Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Foundry Data Analyst
✨Tip Number 1
Network like a pro! Reach out to current employees at Lear or similar companies on LinkedIn. A friendly chat can give you insider info and maybe even a referral!
✨Tip Number 2
Prepare for the interview by brushing up on your data engineering skills. Be ready to discuss your experience with Python, ETL processes, and how you've tackled data challenges in the past.
✨Tip Number 3
Showcase your projects! Bring examples of your work that demonstrate your ability to create data pipelines and transform big data into actionable insights. Visuals can really make an impact!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re serious about joining the team!
We think you need these skills to ace Foundry Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Foundry Data Analyst role. Highlight your experience with data pipelines, programming languages like Python, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Be sure to mention any experience with ML models or cloud-based platforms, as these are key for us.
Showcase Your Projects: If you've worked on any data-focused projects, don't hold back! Include details about your role, the technologies you used, and the impact of your work. We love seeing real-world applications of your skills, so make it count!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Lear Corporation
✨Know Your Data Inside Out
Make sure you’re well-versed in the data engineering concepts relevant to the role. Brush up on your knowledge of data pipelines, ETL processes, and how to handle both structured and unstructured data. Being able to discuss specific projects where you've implemented these skills will impress the interviewers.
✨Showcase Your Programming Skills
Since the job requires expertise in Python and preferably PySpark, be prepared to discuss your experience with these languages. Bring examples of how you've used them to solve real-world problems, especially in a manufacturing context. If possible, practice coding challenges beforehand to sharpen your skills.
✨Understand the Business Context
It’s crucial to translate technical data into actionable insights for stakeholders. Familiarise yourself with Lear's business model and how data analytics supports their operations. Be ready to discuss how your work can contribute to making every drive better, as this shows you understand the bigger picture.
✨Prepare for Agile Discussions
Since the role involves working within an Agile framework, be ready to talk about your experience in Agile environments. Share examples of how you've contributed to team projects, adapted to changes, and delivered results efficiently. This will demonstrate your ability to thrive in a dynamic setting.
