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Senior Data Architect

  • Woking, England, United Kingdom
McLaren Advanced Projects

Job description

At McLaren Racing, we believe only by chasing performance in everything we do can we give ourselves the best chance of success. Performance on track and in the factory. Performance for our people, our business and our partners. It’s about more than winning. It’s about hitting the highest standards, and then raising the bar again.

McLaren Advanced Projects

McLaren Advanced Projects (MAP) is a multidisciplinary engineering unit that works on many of the most ambitious technical challenges at McLaren Racing. MAP is designed to innovate and unlock performance across various racing series operating worldwide.

But racing is just the start. McLaren Advanced Projects also collaborates with McLaren Automotive on hypercars and supercars and undertakes projects on a wide range of scientific and engineering projects for our partners.

Within McLaren Advanced Projects, we assemble integrated teams to work across the full development process from concept to release, drawing on 60 years of continuous development in F1 and beyond. Team members bring a wide range of skills to bear on our projects, from aerodynamics and computational fluid dynamics to lightweight structures and composites, data science and advanced simulations.

Purpose of the Role

The purpose of this role is to define and deliver the data architecture, infrastructure, and services required to help the engineering team operate more effectively and efficiently. You will work closely with McLaren software delivery teams on all elements of the data lifecycle, from collection and storage to analysis and reporting. By optimizing data flows and developing robust data infrastructure, you will empower our engineering team with real-time insights and actionable intelligence, enabling them to optimise their workflows and make informed decisions swiftly. Your expertise will be pivotal in harnessing the power of data to drive innovation, performance, and competitive advantage.

Accountabilities and Responsibilities

  • Develop and maintain scalable, efficient, and flexible data architectures to meet current and future needs of the engineering team, ensuring optimal performance and reliability for streaming, transaction processing, and data warehousing/lakes.
  • Design and optimise data processing pipelines for real-time analysis, enabling quick and effective decision-making. Implement tools and platforms for advanced data analysis, visualization, and reporting.
  • Provide technical guidance on best practice in data engineering and architecture, staying abreast of the latest trends, technologies, and techniques. You will mentor and support team members in data-related tasks and projects.
  • Work closely with engineering and other departments to understand their data needs and challenges. Develop solutions that enhance data accessibility and usability across the team.
  • Continuously monitor data systems and processes, identifying and implementing improvements to enhance efficiency, reduce latency, and support scaling efforts.
  • Research and evaluate emerging data technologies, tools, and methodologies. Lead the adoption of innovative solutions that can provide a competitive edge through superior data insights.
  • Develop and maintain robust disaster recovery plans and backup systems. Ensure compliance with data protection regulations and best practices to safeguard sensitive information.
  • Communicate effectively with both technical and non-technical stakeholders to gather requirements, deliver updates, and translate complex data concepts into actionable insights.
  • Lead data engineering projects, from planning and budgeting to execution and delivery. Ensure projects are completed on time, within scope, and meet the high-quality standards required by the team.

Job requirements

Knowledge, Skills, and Experience


  • Data Pipeline Design and Implementation: Experienced in designing and implementing data pipelines for robust data ingestion, transformation, and distribution, ensuring access to reliable data for analysis and decision-making.
  • Database Management: Deep understanding of SQL for relational database management and NoSQL for non-relational data scenarios, optimizing data storage, access, and scalability.
  • Design Patterns and Architectures: Knowledge of data architecture design patterns (e.g., microservices, ETL, data lakes, data warehouses) to solve common design challenges, ensuring scalable and maintainable data infrastructure.
  • Data Storage Solutions: Familiarity with data storage options, including on-premises, cloud, and edge deployment models for databases, storage, and distributed systems, to select the most appropriate solution based on requirements.
  • Data Ingestion and Streaming: Experience with tools and techniques for efficient data ingestion and real-time streaming (e.g., Kafka), enabling the processing and analysis of live data feeds.
  • Data Processing Frameworks: Proficiency in using data processing frameworks (e.g., Apache Spark, Hadoop) for handling large data sets, facilitating both batch and real-time data processing.
  • Cloud Technologies and Services: Proficient in leveraging cloud technologies and services to build scalable, efficient, and cost-effective data solutions. Experience with cloud platforms and familiarity with cloud-native data warehousing solutions such as Snowflake.
  • Security and Compliance: Awareness of data security practices to ensure data privacy and security across all data architecture designs.
  • Machine Learning: Understanding of the requirements for data and feature engineering to support Machine Learning model development, training, inference, and maintenance. 


  • Effective communication, both written and verbal. Excellent presentation skills. Able to explain complex concepts to all levels of the business. Able to navigate difficult conversations professionally.
  • Open mindedness to ensure high flexibility and the capacity to manage and lead others through rapid and profound changes of scopes, development directions and processes.
  • Aptitude to learn from others and highly skilled at sharing your knowledge effectively. Experience with mentoring/coaching others in the team both technically and personally.
  • Flexible approach to working hours and occasional travel.

What McLaren Can Offer

We strive to provide a fun, innovative, collaborative and open culture where everyone’s input is welcome, and everyone feels part of our achievements. We work hard to create a culture of continuous improvement and support with a proactive approach to management and personal development.

McLaren Advanced Projects is based at the iconic McLaren Technology Centre on the edge of Woking. Our large campus includes a gym, swimming pool, restaurant and indoor and outdoor break-out areas, as well as direct access to park land. MTC is connected to Woking mainline station via regular shuttle buses, from which London Waterloo is a 30 min train ride.

We encourage hybrid working patterns to give you options to balance your home life and hobbies with your work and offer a comprehensive package of benefits including private healthcare, car schemes, life insurance and generous pension contributions.