Length: 6 months initially

Salary: £130,000

We are actively looking to secure a Data Lead to join Experis as one of our expert consultants, delivering services to our clients.

Experis Consultancy is a Global entity with a well-established team with over 1000 consultants on assignment across 20 clients globally. Our UK operation is growing and has very aggressive plans for expansion over the coming years. We form part of the Manpower group of companies that turn over $20 billion a year collectively.

Experis UK have partnerships with major clients across the UK spanning multiple industries; our approach is a very personal one, with both our clients and our own employees. We are passionate about training, technology and career development.

Capabilities Required:

• Existing Architecture & Pattern Reuse – Analyse the WKS5 BCP / Exit / DR data architecture against existing Group-approved strategic data patterns, identifying where established patterns can be reused or extended rather than creating new patterns and triggering lengthy architecture approval cycles.
• Architecture Pathfinding – Determine the fastest compliant route from business requirement to approved technical design, working across Data, Architecture and Technology stakeholders to resolve design constraints early and minimise avoidable governance lead time.
• AI-Ready Data Architecture – Design the data architecture required to support the WKS5 BCP / Exit / DR AI capabilities, ensuring structured and unstructured data can be reliably accessed, related, contextualised and consumed by AI components.
• Business-to-Data Translation – Translate BCP / Exit / DR business processes, requirements, decision logic and user stories into the data entities, relationships, attributes and architecture required to deliver the AI use cases.
• Source-to-Outcome Traceability – Establish clear lineage from system of record -> schema/table -> attribute -> transformation -> AI input -> decision/output, ensuring AI-generated BCP / Exit / DR conclusions can be traced back to authoritative evidence.
• Data Integration & Relationship Design – Architect how supplier, engagement, application, service, incident, assessment, contractual and remediation data are connected without unnecessarily duplicating existing enterprise datasets.
• AI Grounding & Context Architecture – Define how AI capabilities are grounded in authoritative enterprise data, BCP / Exit / DR standards and agreed decision logic, reducing reliance on unsupported model inference.
• Data Quality & Fitness for AI – Identify completeness, accuracy, consistency, lineage and relationship gaps that could materially affect AI outputs and define pragmatic remediation or validation approaches.
• Reusable Data Products – Design reusable data products, interfaces and integration patterns that can support multiple BCP / Exit / DR AI use cases rather than creating bespoke pipelines for individual capabilities.
• Security & Data Controls by Design – Ensure data classification, access, entitlements, retention, lineage and appropriate handling of sensitive data are embedded from the outset.
• Architecture Challenge & Simplification – Challenge unnecessary technical complexity or new architecture where existing approved enterprise capabilities and patterns can achieve the required outcome.
• Delivery-Focused Architecture – Work directly with Product Owners, Data Engineers, AI Engineers/Data Scientists and Solution Architects through design, build and testing — not simply produce architecture documentation and hand it over.