• Experience using business architecture techniques such as capability modelling, value streams, customer journeys or operating-model analysis to connect strategy with technology change.

• Enough technical depth to work confidently with engineering teams and guide solution direction across APIs, data flows, event-driven architecture, cloud services, security, scalability, resilience and cost, while connecting those choices to business value.

• Ability to bring structure to ambiguous business ideas, using evidence, customer insight and business objectives to define clear options, recommendations, transition steps and architecture decisions that product and engineering teams can act on.

• Demonstrated experience taking products, platforms or services from concept through implementation and operation, not only defining strategies, recommendations or high-level designs.

• Ability to challenge assumptions constructively, invite alternative viewpoints and help stakeholders make evidence-based decisions in complex and ambiguous situations.

• Strong communication skills, with the ability to explain business and technical ideas clearly to senior leaders, product teams, architects and engineers.

Desirable experience:

• Knowledge of CRM, consent management, customer identity, data commercialisation, API productisation, partner ecosystems or regulatory compliance in data-driven services.

• Experience with subscription products, marketplace platforms, digital commerce, payments, mobility services or other regulated digital ecosystems.

• Familiarity with enterprise integration patterns, API management, data platforms, cloud-native architectures and secure-by-design practices.

• Experience defining reusable architecture patterns, decision records, reference models or governance approaches that help teams make better decisions at scale.

• Understanding of data product disciplines such as data quality, lineage, data governance, anonymisation and privacy-preserving approaches, and how they influence the commercial viability and responsible use of data products.

• Experience with API product management practices such as versioning, lifecycle management, deprecation, service levels, developer experience and partner onboarding.

• Awareness of how modern AI, machine learning and generative AI capabilities can responsibly enable new data products, improve customer experiences, support operational efficiency and create commercial opportunities.

• Understanding of TM Forum, TOGAF, BIAN or similar industry frameworks would be advantageous, especially where applied pragmatically rather than followed mechanically.

How do we work?

• We value thoughtful challenge, evidence-based decision making and diverse perspectives. You will create space for people to ask questions, raise risks early and challenge assumptions without blame.

• You will work collaboratively rather than relying on authority, helping teams build shared understanding and make better decisions together.

• You will balance progressive thinking with responsible delivery, exploring new commercial and technical opportunities while protecting security, privacy, quality and long-term maintainability.

• You will support continuous improvement by making decisions transparent, learning from evidence and helping teams improve services over time.

What does success looks like?

• Data product and commercial platform initiatives have a clear architecture direction, target-state view, capability roadmap and decision history that business, product and engineering teams can understand and use.

• New propositions are assessed through a balanced view of customer value, commercial model, operating model, regulatory obligations, delivery feasibility and technical sustainability.

• Architecture decisions demonstrably improve customer value, commercial viability and the long-term sustainability of products and services.

• Ideas progress from concept towards real services, avoiding both abstract strategy with no delivery path and technology choices with no clear customer or business value.

• Business and technical stakeholders have a shared understanding of the trade-offs, risks and next steps needed to evolve connected vehicle data into valuable products and services.

We do not expect candidates to have worked in every domain listed. We are looking for depth in at least one relevant commercial platform domain, the curiosity to learn the connected mobility context, the technical credibility to work with engineering teams, and the judgement to connect business ambition with practical architecture and delivery choices.