Solution Architect - Data & AI Specialist - Azure ML - Azure Databricks Hybrid

As a Team Lead Solution Architect
, you’ll play a pivotal role in defining and delivering technology strategies and roadmaps across enterprise applications and operational support services.

This is a senior individual contributor role which will require team management responsibilities and offers the opportunity to influence at scale and work across a wide range of stakeholders and technologies

• Deep domain expertise and demonstrable experience with cloud‑based services for data analytics and AI on the Microsoft Cloud (e.g. Azure ML, AI Foundry, Azure Databricks)
• Experience shaping proof of concepts and evolving designs to productionised solutions with appropriate AI governance incorporating MLOps and LLMOps to manage risk and auditability
• Experience in IT architecture, including applying architectural principles to solution design with a strong focus on designing modern data analytics platforms and AI solutions.
• Strong understanding of the data, analytics and AI technology landscape, including the ability to assess existing estates and develop roadmaps focused on reuse, simplification, and rationalisation.
• Proven ability to translate business strategies, goals, and requirements into coherent architecture designs, solution blueprints, target architectures and technology roadmaps for data analytics.
• Experience shaping enterprise architecture artefacts such as blueprints, technical options, design patterns, high‑level designs, for complex data platforms and analytics use cases.
• Strong stakeholder engagement skills, including the ability to build and maintain stakeholder maps and communicate architectural outputs effectively.
• Experience leading a team of architects, focussing on their personal development and training, and supporting them with their own workload.
• Experience representing architecture at governance forums and advocating for strategic solutions.
• Experience in IT leadership and management, including the development of highly skilled and engaged teams.
• Understanding of best practice across the data lifecycle, including data governance, quality, security, and responsible use of data and AI.

• Experience working with architectural methodologies and frameworks (e.g. TOGAF, Zachman) and experience in architecture modelling tools
• Enterprise Architecture skills such as technical reference model development, building block design, applications and role design, systems integration, and evaluation of architectures.
• Broader expertise of technologies and applications relevant to the Bank’s enterprise applications (e.g. Cloud, Azure, Databricks, data life cycle management, medallion architectures, data lakehouse designs, master data systems, legacy data warehouses, data engineering (ETL, ELT, CDC) for enterprise scale analytics)