McLaren

No restraints. No limitations. We don’t simply push boundaries. We completely rethink them. McLaren Automotive exists to create breath-taking performance road cars.

With innovation at the core of all we do, every challenge starts with the same question. How can we do it better? This restless spirit runs right through McLaren Automotive. And the search for perfection is evident in everything we do.

Are you a seasoned data engineer with a passion for turning raw data into actionable insights, are self-motivated, and have a keen eye for detail and a desire to exceed customer expectations?

You will lead McLaren’s Data & Analytics team, the team responsible for the data landscape and services that underpin McLaren’s data insights.  The portfolio covers technologies that support the life cycle of critical data products, bringing together data producers and consumers through enablement and data ingestion, processing, storage, and publishing, including data visualisation, advanced analytics, data science and data discover platforms.

As a Senior Data Engineer, you will play a crucial role in designing, implementing, and maintaining our data infrastructure, ensuring the efficient and reliable flow of data from various sources to support our organization's data-driven decision-making processes. You will work closely with cross-functional teams to optimize data pipelines, implement best practices, and contribute to the growth and development of our data engineering capabilities. 

Please note this is a hybrid position, you will be expected to work on site at least 2 days a week.

• Developing modern data platforms, utilising the latest Microsoft Azure products.
• Leading design and development of enterprise scale data pipelines in Azure data platforms and services, building data ingestion and publishing pipelines, and support the development and build of automation of system performance and metrics.
• Collaborating with the Infrastructure Team to use existing data products, ingestion patterns, or automations to avoid bespoke development while contributing to the enhancement and creation of these shared assets when gaps are identified.
• Owning the end-to-end technical data lifecycle and corresponding data technology stack.
• Writing, deploying, and maintaining software to build, integrate, manage, maintain and quality assured data, and responsible for deploying secure and well tested software that meets privacy and compliance regulations.
• Adhering to and advocating for software engineering best practices (e.g technical design, technical design review, unit testing, monitoring & alerting, checking in code, code review, documentation).
• Providing data governance across the organisation as part of McLaren’s Data Authority.
• Evangelising business insight through data, providing leadership and direction throughout the organisation to ensure common approaches and trusted data sources.

• Strong technical expertise using core Microsoft Azure data technologies: Data Factory, Databricks, Data Lake, Azure SQL, Synapse, Analysis Services, Batch, Event Hubs, Data Explorer, Purview and Power BI.
• A strong background in Python development, particularly for data engineering, and SQL.
•  Experience of team working and task tracking with Azure DevOps following Scrum / Agile methodologies.
• Experience with Azure databases (Synapse and Azure SQL).
• Experience with Continuous Integration, Continuous Deployment, Peer Review, Automated Testing for DataOps solution delivery.
• C# development skills are a plus.
• Experience of wider Azure services used for infrastructure build and monitoring (ARM, Policy, Monitor, Log Analytics etc).

• Data Governance: Proven understanding of data governance standards and best practices, and management processes and how to apply them in data platforms.
• Data Domain knowledge: proven understanding of data sources and data and analytics requirements and typical SLAs associated to data provisioning and consumption at enterprise scale.

• A motivated and engaging individual, who is dependable and a team player.
• Customer focused approach with good communication and prioritisation skills, ability to challenge constructively and influence stakeholders.
• An analytical mindset, with strong problem-solving abilities. 
• A meticulous approach with a keen attention to detail.
• The ability to lead, and work with multiple product teams with competing priorities.