Manager - Data-centric Business Architect in London

Where your journey begins and your potential shines. At Synpulse, we don’t just consult – we transform. As a leading global management and technology consultancy with Swiss roots, we empower financial institutions to navigate change and seize new opportunities. Since 1996, we've been shaping the future of financial services by delivering cutting-edge expertise in strategy, operations, and technology to banks and insurers worldwide.

What sets us apart is our people. At Synpulse, we cultivate a collaborative, high-impact culture where initiative and creativity are valued. With 21 offices across Europe, the Americas, and Asia-Pacific, we bring together diverse perspectives and talents. We believe innovation thrives where everyone feels they belong and can contribute. Our core values – Embrace, Drive, Achieve – shape how we work and grow. We don’t just offer jobs – we offer the opportunity to grow, make a difference, and be part of a team that’s redefining the future of financial services.

The Data-centric Business Architect is a consulting role focused on helping insurers and reinsurers translate business strategy into data- and AI-enabled operating models, target-state designs, and scalable transformation outcomes. This role sits at the intersection of domain consulting, business architecture, data strategy, and AI-enabled transformation. It is responsible for structuring business problems, defining required data and AI capabilities, and ensuring that business intent is translated into coherent, implementable solutions.

This role is particularly relevant across Commercial & Specialty Insurance, Reinsurance, and Delegated Authority, where organisations are evolving from system-centric environments towards data- and AI-enabled operating models that support improved decision-making, automation, control, and scalability. The individual will work closely with Synpulse’s Management consulting teams, clients and engineering teams to define business and data requirements, shape semantic and architectural models, and ensure alignment across business, data, and technology throughout the lifecycle.

• Structure ambiguous client problem statements into clear, actionable workstreams and deliverables.
• Engage stakeholders across (re)insurance functions/domains to capture requirements and validate designs.
• Facilitate workshops and design sessions, ensuring alignment across business and technology stakeholders.
• Assess existing data landscapes and operating models to identify gaps, inconsistencies, and improvement opportunities.
• Support delivery teams by ensuring that business and data requirements are implemented accurately and remain aligned to intended outcomes.

• Lead the design of data- and AI-enabled target operating models, business capability maps, and transformation roadmaps across (re)insurance domains.
• Define required data assets, business definitions, and semantic structures aligned to business outcomes and operational needs.
• Translate domain requirements into structured outputs, including conceptual and logical models, business rules, and architecture-aligned specifications.
• Ensure alignment between business intent, data architecture, and AI-enabled capabilities across the solution lifecycle.
• Identify where AI can be applied to enhance decision-making, automation, analytics, and operational efficiency, ensuring use cases are grounded in practical feasibility.

• Contribute to the development of reusable proposition assets, including semantic models, business glossaries, data definitions, and reference approaches.
• Support the evolution of Synpulse’s Data & AI offerings by embedding data- and AI-centric thinking into domain propositions.
• Help shape integrated solutions that combine business architecture, data foundations, analytics, and AI capabilities.
• Contribute to internal knowledge building and strengthening of the Data & AI capability across the practice.

• In depth understanding of Commercial & Specialty Insurance, Reinsurance, and/or Delegated Authority value chains.
• Proven ability to design target operating models, business capabilities, and architecture-aligned solutions in complex environments.
• Strong understanding of semantic modelling, logical data modelling, and business data concepts, and how these support analytical and AI-driven outcomes.
• Good understanding of AI-enabled transformation and the dependencies between business processes, data structures, governance, and technology.
• Ability to work effectively across business and technology domains, engaging with architects, engineers, and stakeholders without being a pure technical specialist.
• Well developed analytical and problem-structuring capability, with the ability to translate complex topics into clear and actionable outputs.
• Exceptional communication and facilitation skills, including leading workshops and engaging senior stakeholders.
• Comfortable operating independently or as part of a wider delivery team in fast-paced consulting environments.
• Proven relevant experience in consulting, insurance, reinsurance, insurtech, or related financial services roles.
• Experience in business architecture, data strategy, business analysis, or similar roles within reinsurance or financial services.
• Demonstrated experience translating business requirements into structured designs, including operating models, business/data models, and solution inputs.
• Exposure to cloud, data, and analytics environments, with sufficient understanding to shape solution direction and challenge approaches.
• Experience contributing to data- and AI-enabled transformation initiatives, including operating model design, analytics, governance, or broader transformation programmes.
• Experience working with both business stakeholders and technical teams in delivery environment.
• Bachelor’s degree or equivalent experience; advanced degree in Business, Information Systems, Data Science, or a related discipline is advantageous.
• Professional or industry certifications in business architecture, data management, or reinsurance (e.g. TOGAF, DAMA, or equivalent frameworks) are advantageous but not essential.