Lead AI and Data Architect, Senior Manager – Strategy, Governance and Architecture, AI & Data

Overview

In this role you will lead the architecture of complex AI and data transformation programmes for high-profile clients. You’ll translate business goals into scalable, secure solutions and steer cross-functional teams from strategy through delivery. You’ll shape innovative technology solutions, share expertise, and mentor colleagues within an inclusive, high-performing culture. The opportunity blends client impact with cutting-edge data and AI work, offering growth through world-class training and collaboration.

Pay / Benefits

• hybrid working policy
• world-class training and development
• inclusive and supportive culture
• career mobility and growth
• flexible location (London or Manchester)
• wellbeing focus

Responsibilities

• Lead end-to-end functional and solution architectures for data and analytics initiatives
• Translate business requirements into project plans, roadmaps, and technical specs for delivery
• Partner with executive stakeholders and cross-functional teams to ensure successful outcomes
• Provide thought leadership and contribute to innovative technology solutions
• Mentor junior team members and foster an inclusive, high-performing team culture
• Contribute to proposals for new business opportunities and client growth
• Stay informed on industry trends and vendor landscape to shape solution approaches

Key requirements

• Significant experience in data, AI or enterprise architecture in consulting or client-facing environments
• Proven ability to build and maintain strong client relationships and present to senior stakeholders
• Experience leading architecture or technical teams and coordinating multidisciplinary delivery
• Experience developing data architecture blueprints and presenting to Technical Design Authorities or Architecture Boards
• Experience with architectural evaluation and design of enterprise systems (on-premise and cloud) and build-vs-buy decisions
• Experience engaging with business and IT stakeholders to define outcomes for large-scale solutions

• Client relationship management
• Mentoring and developing others
• Thought leadership and collaboration
• Cloud platforms: AWS, Azure, GCP, Databricks, Snowflake and their AI/ML services
• Data architecture: data modelling, management, quality, MDM, reference data, reporting and AI
• Governance & security: data governance, data lineage, GDPR, ethical AI

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