Solution Architect - Data & AI Specialist - London - Hybrid

W Talent; Greater London; Hybrid; GBP 81,000 - 99,000; Full time

Benefits offered by this job

Excellent Benefits

Job summary

W Talent is seeking a Team Lead Solution Architect specialising in data analytics and AI to define and deliver architectural roadmaps across enterprise platforms and cloud services. You will translate business goals into scalable designs, govern AI projects, and collaborate with stakeholders across IT and business units.

The senior role combines hands-on architecture leadership with mentoring, governance participation, and strategic influence.

Qualifications

• Extensive experience in data analytics and AI platforms.
• Proven ability to translate business requirements into architecture designs.
• Experience leading architects and governance forums.

Responsibilities

• Lead enterprise data analytics and AI solution architecture.
• Develop roadmaps and target architectures.
• Mentor and manage architects and ensure governance outputs.

Skills

Stakeholder engagement

Team leadership

Data analytics

Azure cloud

AI governance

MLOps

LLMOps

Solution architecture

Architectural design

Data governance

Tools

Azure Databricks

Azure ML

AI Foundry

Job description

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

Lead Solution Architect - Data & AI Specialist

Location: - London - Hybrid 2/3 days per week on-site - Flex working hours

Permanent - Full Time

Salary: £90,000 + Excellent Benefits

Key skills and experience:

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 evolve 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.

It would also be beneficial, but not necessary, to have some of the following:

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)