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:
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• Lakehouse architecture and Delta Lake

• Data warehousing
• ETL/ELT pipelines
• Change Data Capture (CDC) and change tracking
• Stream processing
• Database design
• Machine Learning and AI integration
• Hands-on experience with:
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• Azure Databricks

• Python / PySpark
• Microsoft SQL Server
• Azure Blob Storage
• Parquet file formats
• Azure Data Factory
• 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.

DESIRABLE EXPERIENCE:

• 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.

ABOUT US

Our story began more than 20 years ago, but right from the start, it has been rooted in the specific needs of the automotive industry. As automotive professionals as well as technologists, we wanted to build practical technology solutions that were designed around how automotive businesses work, recognising what makes them different. Pinewood.AI is an unparalleled Automotive Intelligence Platform that enables automotive retail customers and OEMs to drive growth and profitability throughout every aspect of their business.
Pinewood’s cloud-based, secure end-to-end ecosystem unlocks the value of every customer. Our vision is to be the full-service technology partner that helps automotive retailers and OEMs run more efficiently and increase revenue by making better commercial and business decisions more easily

• 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