Senior Data Architect

Overview

In this role you shape Burberrys data landscape, leading cross-domain data architectures across products, platforms, analytics and governance. You translate business outcomes into coherent data designs and set patterns for scalable, secure information flows. You will mentor other architects and ensure architecture decisions align with enterprise strategy. This is a senior, influence-led role focused on data as a strategic asset in a complex, multi-domain environment.

Responsibilities

• Lead end-to-end data architecture for cross-domain programmes and translate business roadmaps into implementable designs
• Own data architecture for major change initiatives across source systems, operational stores, Databricks and downstream layers
• Provide senior design authority, challenging teams on architectural quality, security and long-term fit
• Define domain and cross-domain models for core Burberry domains (Product, Customer, Merchandise, Sales, Inventory, Supply Chain, Finance, People)
• Define authoritative sources, system-of-record boundaries, data contracts and data flows for consistent representation across products and platforms
• Shape data architecture for reusable data products and analytics on the data estate, including lakehouse, semantic structures and data assets
• Set data architecture patterns, modelling guidance and lifecycle controls aligned to business needs
• Embed data quality, glossary, privacy, retention and governance requirements into designs
• Support migration, platform modernisation, consolidation and legacy retirement with mapping and transition sequencing
• Engage early in demand shaping and risk assessment, identifying data dependencies and non-functional requirements
• Maintain reusable artefacts and address cross-estate duplication and technical debt with leadership

Key requirements

• Strong practical expertise in conceptual, logical and physical data modelling
• Experience designing end-to-end data architectures on cloud platforms; Databricks experience advantageous
• Knowledge of data governance concepts: sources, lineage, contracts, metadata and privacy
• Experience with data migration, platform modernisation and legacy retirement
• Ability to influence senior stakeholders and challenge architectures
• Experience across Product, Engineering, Enterprise Architecture, Governance and cross-functional teams
• Coaching or mentoring experience for architects or senior technical specialists
• Experience in Retail, Fashion, Luxury or Consumer Goods data domains is beneficial

• strong communication
• influencing skills
• mentoring and coaching
• conceptual, logical and physical data modelling
• lakehouse and data warehouse architectures
• data products, analytics and semantic layers

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