Lead Platform Engineer, Data Platform

As a Data Platform Lead, you will be responsible for defining, building, and operating Dyson's enterprise data platform capabilities. You will lead the design and evolution of modern data platforms that enable data ingestion, storage, processing, governance, analytics, and AI workloads at scale. Working closely with architects, platform engineers, data engineers, data scientists, and business stakeholders, you will ensure that data platforms are reliable, secure, cost-effective, and easy to consume. About the Team The Platform Engineering and Infrastructure team is responsible for building and operating Dyson's core technology platforms across cloud, infrastructure, data, and developer services. The team provides shared capabilities that enable engineering and business teams to build, deploy, and operate solutions efficiently and securely. Working closely with engineering, analytics, AI, and business teams, we provide scalable platform services that simplify technology adoption, improve productivity, and accelerate innovation. Through automation, modern cloud technologies, and engineering best practices, we enable teams to focus on delivering business value rather than managing infrastructure. About the Role As a Data Platform Lead, you will: • Define and drive the strategy, roadmap, and architecture for Dyson's enterprise data platforms. • Design, build, and operate scalable data platform services supporting analytics, reporting, AI, and machine learning workloads. • Lead the implementation of cloud-native data platform solutions across GCP and AWS where required. • Establish platform standards, governance frameworks, security controls, and operational best practices. • Enable self-service data capabilities that improve productivity for data engineers, analysts, and data scientists. • Build and manage platform services for data ingestion, transformation, orchestration, storage, and consumption. • Collaborate with enterprise architects and business stakeholders to understand data platform requirements and priorities. • Ensure platforms meet requirements for availability, performance, security, compliance, and cost efficiency. • Drive automation through Infrastructure as Code, platform engineering, and operational tooling. • Lead platform modernization initiatives and adoption of emerging technologies in analytics and AI. • Mentor engineers and develop technical capabilities within the team. • Manage platform lifecycle, operational support, incident management, and continuous improvement activities. • Drive FinOps and platform optimization initiatives to maximize value from cloud investments. About You You will have: • A degree in Computer Science, Software Engineering, Information Technology, Data Engineering, or a related discipline. • Significant experience building and operating enterprise-scale data platforms. • Strong understanding of modern data architecture, data engineering, and analytics ecosystems. • Experience with cloud-native data platforms and services in Google Cloud Platform, AWS, or Azure. • Experience with data warehousing, data lakes, lakehouse architectures, and large-scale data processing. • Strong understanding of data governance, security, privacy, and compliance requirements. • Experience with data orchestration, automation, and platform engineering practices. • Knowledge of Infrastructure as Code, CI/CD, and cloud automation frameworks. • Experience supporting analytics, business intelligence, AI, and machine learning workloads. • Strong stakeholder management, communication, and leadership skills. • Excellent problem-solving capabilities and a passion for driving continuous improvement. Desirable Experience • Experience with BigQuery, Databricks, Snowflake, or similar enterprise data platforms. • Experience with real-time data streaming and event-driven architectures. • Knowledge of data catalog, metadata management, and data governance solutions. • Experience supporting enterprise AI and machine learning platforms. • Cloud certifications in GCP, AWS, Azure, or data engineering disciplines. • Experience operating platforms within a multi-cloud environment. Key Behaviours • Demonstrates strong technical leadership and ownership. • Thinks strategically while remaining hands-on when required. • Builds strong relationships across engineering, data, and business teams. • Promotes automation, standardization, and operational excellence. • Champions data-driven decision making and continuous improvement. • Encourages collaboration, innovation, and knowledge sharing. • Maintains a customer-focused mindset and delivers measurable business outcomes.

Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.