# Enterprise Data Architect Consultant

**Company**: Infosys Consulting - Europe
**Location**: London, England
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Category**: Consulting
**Industry**: Consulting

**Apply**: https://jobs.workable.com/view/tZ1FCrHpArdhmJbntwFv6P/hybrid-enterprise-data-architect-consultant-in-london-at-infosys-consulting---europe?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_0629570b-47b

## Description

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.

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## Skills

### Required
- data architecture
- enterprise architecture
- solution architecture
- data engineering
- cloud data platforms
- lakehouses
- warehouses
- data governance
- metadata management
- semantic layers
- knowledge graphs
- GenAI
- AI
- ML

### Nice to have
- graph modelling
- ontology standards
- graph query languages
- RDF
- OWL
- SPARQL
- feature store design
- MLOps
- DataOps
- stream processing
- Apache Kafka
- Apache Flink
- master data management
- data mesh architecture

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