At a Glance
- Tasks: Build and maintain a cutting-edge data platform for the automotive industry.
- Company: Join Pinewood.AI, a leader in automotive technology solutions.
- Benefits: Competitive salary, 25 days holiday, life assurance, and ongoing training.
- Other info: Dynamic team environment with opportunities for continuous improvement and growth.
- Why this job: Shape the future of data with innovative AI technologies and impactful projects.
- Qualifications: Experience in data engineering, Python, and building scalable data pipelines.
The predicted salary is between 36000 - 60000 € per year.
Pinewood.AI is looking for a skilled and experienced Data Engineer to help shape the future of data solutions in the automotive technology space. In this role, you’ll be instrumental in developing scalable, modern data infrastructure that supports our global Automotive Intelligence Platform - the system that powers thousands of dealerships worldwide. You’ll take ownership of the full data lifecycle, from extracting and transforming data to optimising performance and developing secure, scalable storage solutions. If you’re passionate about building clean, robust cloud-based pipelines, working with large and complex datasets, and applying the latest technologies (including AI features), this is the role for you.
Key Responsibilities
- Build and maintain a unified data platform that ingests and processes global data from across our Automotive Intelligence Platform.
- Develop scalable and reusable data solutions with a strong emphasis on componentisation.
- Optimise the performance and reliability of data pipelines, ensuring fast access to large datasets.
- Collaborate with the data visualisation team to align back‑end processing with front‑end reporting.
- Design and implement secure, flexible data access models for internal and external users.
- Use bespoke pipelines and Azure Data Factory to incorporate 3rd party external data sources.
- Establish unit and integration testing practices and support CI/CD processes for data pipelines.
- Identify and resolve bottlenecks or performance issues across the data stack.
- Investigate and address platform support tickets related to data.
- Enable multi‑language capabilities within the platform’s data presentation layer.
- Explore and integrate AI capabilities to boost data productivity and accuracy.
Requirements
- Strong understanding of data engineering concepts, including Lakehouse architecture and Delta Lake, Data warehousing, Change Data Capture (CDC) and change tracking, Stream processing, Machine Learning and AI integration.
- Hands‑on experience with Python / PySpark and Microsoft SQL Server.
- Proven experience building secure, scalable, and high‑performing data pipelines.
- Ability to solve complex technical problems and work collaboratively across teams.
- Excellent communication and documentation skills.
- Self‑motivated with a proactive approach to continuous improvement.
- Experience in the retail sector, especially automotive retail.
- Background in delivering large‑scale, enterprise‑grade data solutions.
- Familiarity with Agile methodologies and working in cross‑functional teams.
Competitive salary based on experience. 25 days holiday plus all UK bank holidays. Life assurance. Ongoing training.
Data Engineer - Azure, Databricks, ML/AI employer: Pinewood.AI
Pinewood.AI is an exceptional employer that fosters a dynamic and innovative work culture, perfect for Data Engineers eager to make a significant impact in the automotive technology sector. With a strong emphasis on employee growth, we offer ongoing training and development opportunities, alongside a competitive salary and generous holiday allowance. Our collaborative environment encourages creativity and problem-solving, making it an ideal place for those passionate about leveraging cutting-edge technologies like AI to drive data solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Azure, Databricks, ML/AI
✨Tip Number 1
Network like a pro! Reach out to folks in the automotive tech space, especially those working with data engineering. Attend meetups or webinars, and don’t be shy about sliding into DMs on LinkedIn. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Azure, Databricks, and ML/AI. This is your chance to demonstrate your expertise in building scalable data pipelines and solving complex problems. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Prepare for interviews by brushing up on common data engineering questions and scenarios. Think about how you’d tackle performance issues or design secure data access models. Practising your responses will help you feel more confident and ready to impress!
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our job listings and make sure your application stands out by tailoring it to the specific role and highlighting your relevant experience.
We think you need these skills to ace Data Engineer - Azure, Databricks, ML/AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Data Engineer role. Highlight your experience with Azure, Databricks, and any relevant ML/AI projects to catch our eye!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our Automotive Intelligence Platform. Be genuine and let your personality come through.
Showcase Your Projects:If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work, especially if it involves building data pipelines or using AI technologies. We love seeing what you can do!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Pinewood.AI
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of Azure, Databricks, and ML/AI concepts. Be ready to discuss how you've used these technologies in past projects, especially in building scalable data pipelines. The more specific examples you can provide, the better!
✨Showcase Your Problem-Solving Skills
Prepare to talk about complex technical problems you've solved in your previous roles. Think about challenges related to data performance or pipeline optimisation, and be ready to explain your thought process and the solutions you implemented.
✨Collaboration is Key
Since this role involves working with cross-functional teams, be prepared to discuss your experience collaborating with others, particularly with data visualisation teams. Highlight any successful projects where teamwork made a significant impact.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the company’s approach to integrating AI capabilities or how they handle data security. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
