Enterprise Data Architect Consultant

We are looking for client-facing Enterprise Data Architects to join our growing Enterprise AI practice. You will help clients transform fragmented data estates into AI-ready foundations, advising on architecture decisions across cloud data platforms, lakehouse and warehouse patterns, data products, semantic layers, metadata, lineage, governance, knowledge graphs and GenAI retrieval patterns.

Responsibilities:

• Design AI-ready enterprise data architectures that enable analytics, AI, ML, GenAI and agentic applications to consume data accurately, securely and with appropriate business context.
• Assess clients’ existing data estates, diagnose structural, governance, semantic and quality issues, and design pragmatic modernisation roadmaps.
• Advise clients on architecture and platform choices, helping them navigate trade-offs between lakehouses, warehouses, data fabrics, graph databases, semantic layers, vector search and hybrid architectures.
• Define data governance and metadata patterns covering ownership, stewardship, quality, lineage, cataloguing, access control and data lifecycle management.
• Design data products, data contracts and information models that make enterprise data reusable across analytics, AI, GenAI and operational workflows.
• Shape semantic layers, ontologies and knowledge graph patterns where these improve data discoverability, interoperability, explainability or AI consumption.
• Oversee high-level design of ingestion, integration and transformation patterns, including batch, event-driven and real-time architectures.
• Identify and mitigate data-related risks, including poor data quality, weak provenance, data leakage, inappropriate access, retrieval failure and inference-time use of enterprise knowledge.
• Act as a trusted advisor to client stakeholders, translating technical architecture concepts into clear business outcomes, options and risks.
• Contribute to proposals, client conversations, internal methods and thought leadership on enterprise data architecture and AI-ready data foundations.

Requirements:

• 15+ years experience in data architecture, enterprise architecture, solution architecture or senior data engineering roles.
• Strong experience in working with clients to formulate Data Governance policy and Data Strategy roadmaps.
• Experience modernizing data landscapes and establishing robust governance frameworks in regulated industries.
• Demonstrable experience designing modern data architectures for analytics, AI, ML or GenAI consumption.
• Strong understanding of enterprise data architecture patterns, including cloud data platforms, lakehouses, warehouses, data integration, data modelling and metadata management.
• Experience contributing to or leading data governance initiatives, including catalogues, lineage, ownership, stewardship, data quality and metadata management.
• Practical understanding of semantic layers, ontologies or knowledge graph concepts, with hands-on experience in at least one of these areas.
• Deep experience with at least one major cloud data platform, such as AWS, Azure or Google Cloud, and familiarity with leading lakehouse or warehouse technologies.
• Understanding of how data architecture decisions affect AI and GenAI outcomes, including data quality, provenance, context, retrieval, security, privacy and semantic consistency.
• Familiarity with GenAI data patterns such as retrieval-augmented generation, vector search, embedding pipelines, chunking strategies or enterprise search.
• Strong stakeholder management and communication skills, with the ability to present complex technical trade-offs clearly to non-technical sponsors and senior executives.
• Excellent written and verbal communication skills in English.
• Bachelor’s degree or equivalent experience; quantitative, technical or analytical disciplines are an advantage.
• Willingness to travel, up to around 60% depending on project requirements, across the UK and internationally.

Benefits:

• Industry-leading compensation and benefits.
• Top training and development opportunities.