Be part of a globally renowned management consulting firm on the front-line of industry disruption and at the cutting edge of technology. We work with market leading brands across sectors. Our culture is inclusive and entrepreneurial. Being a mid-size consultancy within the scale of Infosys gives us the global reach to partner with our clients throughout their transformation journey. Recognized as one of the UK’s top firms by the Financial Times and Forbes Listed on Germany’s top employers list for 2023 Named on Management Consulting Magazine's list of Best Firms to Work for Recognized by the Top Employers Institute for exceptional standards in employee conditions across Europe for five years in a row
Enterprise Data Architect
Location
United Kingdom
Posted
3 days ago
Salary
0
Seniority
Mid Level
Job Description
Enterprise Data Architect
Infosys Consulting - Europe
Role Description Enterprise AI is forcing organisations to rethink their data estates. Data platforms designed mainly for reporting are often not enough for GenAI, semantic search, agentic workflows and AI-enabled decision-making. Clients now need data that is trusted, governed, contextualised and consumable by both people and intelligent systems. 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 - GenAI retrieval patterns This is a consulting role, not a purely internal architecture role. You will: - Diagnose ambiguous client problems - Shape options and make trade-offs explicit - Translate complex data architecture issues into clear decisions for both technical teams and executive stakeholders You will work in cross-functional teams alongside: - Product owners - Data scientists - ML and GenAI engineers - Data engineers - Business analysts - Client stakeholders Typical outputs may include: - Target-state architectures - Maturity assessments - Platform option appraisals - Data product designs - Governance models - Lineage maps - Ontology and semantic models - Integration patterns - GenAI data-readiness assessments - Implementation roadmaps We are hiring across several levels. At earlier levels, we expect: - Strong architecture delivery experience - Hands-on platform understanding At senior levels, we expect: - The ability to shape enterprise data strategy - Influence senior stakeholders - Lead complex architecture decisions - Guide multi-disciplinary delivery teams We do not expect every candidate to be a specialist in every aspect of AI-ready data architecture. We are looking for architects with: - Strong core data architecture experience - Credible depth in some areas that matter for AI-enabled data estates, such as governance, semantic modelling, lakehouse architecture, data products, metadata management, knowledge graphs, RAG or enterprise data strategy 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 - Design pragmatic modernisation roadmaps - Advise clients on architecture and platform choices - Define data governance and metadata patterns - Design data products, data contracts and information models - Shape semantic layers, ontologies and knowledge graph patterns - Oversee high-level design of ingestion, integration and transformation patterns - Identify and mitigate data-related risks - Act as a trusted advisor to client stakeholders - Contribute to proposals, client conversations, internal methods and thought leadership Qualifications - 5–10+ years, depending on level, in data architecture, enterprise architecture, solution architecture or senior data engineering roles - Demonstrable experience designing modern data architectures for analytics, AI, ML or GenAI consumption - Strong understanding of enterprise data architecture patterns - Experience contributing to or leading data governance initiatives - Practical understanding of semantic layers, ontologies or knowledge graph concepts - Deep experience with at least one major cloud data platform - Understanding of how data architecture decisions affect AI and GenAI outcomes - Familiarity with GenAI data patterns - Strong stakeholder management and communication skills - 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 Requirements - A second major European language is an advantage - Experience with graph modelling, ontology standards or graph query languages - Familiarity with feature store design and MLOps / DataOps pipeline integration - Experience with stream processing at scale using Apache Kafka or Apache Flink - Background in master data management or data mesh architecture - Consulting or comparable client-facing delivery experience - Exposure to some relevant technologies Benefits - Industry-leading compensation and benefits - Top training and development opportunities
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