Data Analytics & AI at Dyson  

Data and analytics excellence at Dyson is delivered by a diverse and collaborative global community, at the heart of that community is a hub team that enables all others: In Dyson’s Data Analytics team, there has been significant investment into cloud technologies and AI; combined with an expansive scope and no shortage of ambition and momentum, Dyson’s Data Analytics & AI team is recognised throughout the organisation to the highest level as critical to all of Dyson's strategic objectives.  

With a ‘one-team’ approach, the global community is on a mission to:  

• Evolve existing solutions to stay ahead  

• Embed emerging solutions to capitalise on potential benefits  

• Deliver conceptualised & future solutions to introduce net-new capability  

The Team  

As the ‘hub’ team delivering the data, technology and community provision enabling Dyson’s global data and analytics capabilities, Dyson’s Data Analytics & AI team have end-to-end responsibility for data from foundations (DQ, MDM) to management (data platforms, integrations), to value realisation (analytics enablement and delivery) and leveraging AI.  

Dyson’s Data Analytics & AI team is a multi-disciplinary, global team providing round-the-clock development and operations - including product and project management, community enablement, governance, data architecture, data engineering, data science, and analytics expertise.  

Involved with every aspect of Dyson’s global business - from finance to product development, manufacturing to owner experience – the team is seeking to deliver solutions generating impressive and tangible business value.  

About the role 

• Define, evolve and govern Dyson’s enterprise data architecture principles, standards, reference models and design patterns, ensuring they are practical, scalable and consistently applied across data platforms and solutions. 

• Lead the architecture of complex, multi-system data solutions across warehouses, lakes, real-time platforms and analytical environments, balancing business value, scalability, security, performance, cost and long-term maintainability. 

• Translate business objectives and stakeholder needs into conceptual, logical and physical architecture designs, ensuring solutions are actionable, sustainable and aligned to enterprise architecture direction. 

• Provide hands-on architectural leadership throughout transformation programmes and delivery projects, guiding design decisions, resolving architectural trade-offs and ensuring adherence to agreed standards. 

• Establish and strengthen data governance, metadata, taxonomy, lineage, ownership and compliance practices so that Dyson’s data assets are reliable, discoverable, secure and responsibly managed. 

• Partner with business, data, engineering, governance and enterprise architecture teams to align priorities, influence roadmaps and ensure data architecture supports Dyson’s strategic goals. 

• Review and challenge solution designs to ensure they are robust, secure, scalable, cost-effective and future-ready, while supporting teams in managing risk and technical debt. 

• Define, monitor and improve architectural approaches for performance engineering and cost optimisation, including the design of efficient ETL/ELT workloads and data platform usage patterns. 

• Create, maintain and improve architecture artefacts including blueprints, data models, data flows, sequence diagrams, decision records and standards documentation. 

• Act as a technical leader and change agent for the data architecture practice, promoting collaboration, continuous improvement, documentation quality and practical adoption of best practice. 

About you 

• Proven experience leading data architecture within complex digital transformation, enterprise data platform or multi-domain data programmes. 

• Strong expertise in enterprise data architecture design, including data warehouses, data lakes, real-time data platforms, semantic layers, data models and cross-system data flows. 

• Ability to design and articulate end-to-end data solutions that address complex business challenges while aligning with enterprise architecture principles and long-term platform strategy. 

• Deep understanding of data governance, metadata management, taxonomy, lineage, ownership, stewardship, access controls, compliance and responsible data usage. 

• Experience architecting scalable, secure and cost-effective cloud-based data solutions, ideally using GCP and modern data warehouse, orchestration, modelling and ingestion technologies. 

• Confident reviewing technical designs, challenging assumptions and making pragmatic recommendations that balance stakeholder needs, technical constraints, risk and business value. 

• Strong stakeholder engagement skills, with the ability to translate business objectives into architecture decisions and communicate complex concepts clearly to technical and non-technical audiences. 

• Experience influencing architecture roadmaps, aligning cross-functional teams and working effectively with data engineering, data governance, product, analytics and enterprise architecture communities. 

• A continuous improvement mindset, with a track record of improving standards, documentation, engineering practices, architecture governance and knowledge sharing. 

• Clear ownership, resilience and learning agility, with the ability to operate effectively through ambiguity, lead change and support others in adopting new technologies, frameworks and ways of working. 

• Experience mentoring architects, engineers or analysts and raising architecture capability across teams through constructive feedback, coaching and practical guidance. 

Our Tech Stack   

Our modern data stack constantly evolves over time as it strives for best-in-class technical capabilities, scalability and efficiency. We don’t require applicants to have experience with all these technologies, but are always keen to learn and maximise best use of each and as a whole  

• Bitbucket for source control management  

• Terragrunt for infrastructure as code  

• GCP for infrastructure  

• BigQuery for data warehousing  

• Airflow for orchestration  

• dbt (SQL) for data modelling  

• Grafana for monitoring  

• Fivetran for ingestion 

You Should Apply If  

• You feel strongly about data and want to empower the organisation with it   

• You seek technical excellence and is self-driven and motivated  

• You want to build robust, scalable and reliable software and solutions  

• You proactively identify challenges and opportunities, and seek to improve the team as a whole