Burberry Senior Data Architect
- Accountable for senior solution-level data architecture across complex programmes, products and cross-domain change, including the coherence of data structures and information flows between domains and systems.
- Accountable for the quality and consistency of conceptual, logical and physical models, data architecture decisions, authoritative-source definitions, data contracts and source-to-consumption data flows within assigned scope.
- Operates within enterprise data architecture principles, target states and guardrails; enterprise-wide strategy and formal architecture direction remain with the relevant Director and governance bodies.
- Does not own enterprise data governance policy, business data ownership or stewardship. These remain with Data Products & Governance; the Senior Data Architect ensures governance requirements are designed into solutions and provides senior architecture input where policy or ownership decisions affect solution design.
- Does not own day-to-day data platform operations or engineering delivery. These remain with Data Engineering & Platforms, delivery squads and strategic partners; the Senior Data Architect provides the architecture they implement and assures major technical decisions.
- Lead end-to-end data architecture for complex, cross-domain programmes and products, translating business outcomes and strategic roadmaps into coherent data designs that delivery teams can implement.
- Own data architecture for major change initiatives, shaping current-state, transition and target-state architectures across source systems, operational stores, Databricks and downstream analytical and consumption layers.
- Provide senior design authority on data architecture decisions, reviewing and challenging Data Architects, engineering teams, Solution Architects, system integrators and vendors where architectural quality, scalability, security or long-term fit are at risk.
- Lead the definition and alignment of domain and cross-domain data models, including conceptual, logical and physical models for core Burberry domains such as Product, Customer, Merchandise, Sales, Inventory, Supply Chain, Finance and People.
- Define authoritative sources, system-of-record boundaries, master/reference data relationships, ownership points and critical information flows so business concepts are represented consistently across products, platforms and channels.
- Shape data architecture for reusable data products and analytical capabilities on Burberry's modern data estate, including lakehouse, curated data layers, semantic structures and data assets supporting reporting, analytics and AI.
- Set and evolve data architecture patterns and modelling guidance, selecting approaches appropriate to business need, reuse, scale, performance and lifecycle requirements.
- Define and assure data contracts, schemas, lineage requirements, metadata structures and lifecycle controls, working with Data Engineering & Platforms and Integration Architecture on implementation patterns.
- Resolve complex cross-domain data dependencies and trade-offs, balancing business needs, delivery feasibility, data quality, security, resilience, cost and long-term simplification; escalate material exceptions through governance.
- Work with Data Products & Governance to embed data quality, catalogue, glossary, classification, privacy, retention and stewardship requirements into solution designs.
- Provide senior architecture input to migration, platform modernisation, consolidation and legacy retirement programmes, including source-to-target mapping, coexistence, reconciliation and transition sequencing.
- Engage early in demand shaping and investment assessment, identifying data dependencies, architecture complexity, non-functional requirements and delivery risks before commitments are made.
- Maintain reusable data architecture artefacts and identify cross-estate duplication, conflicting models and technical debt, shaping remediation roadmaps with architecture, engineering, governance and product leadership.
- Coach and mentor Data Architects and provide technical direction to data engineers, analytics engineers and partners, raising the consistency and quality of data architecture without creating unnecessary delivery dependency.
- Represent data architecture in governance and design authority forums, presenting options, recommendations, exceptions and decision impacts to senior technical and business stakeholders.
- Significant experience as a Data Architect, Senior Data Architect, Data Solution Architect or similarly senior data-focused architecture specialist within a complex enterprise technology environment.
- Strong practical expertise in conceptual, logical and physical data modelling, with a track record of shaping cross-domain models and resolving complex data design decisions.
- Deep understanding of modern data architecture across lakehouse, data warehouse, data products, analytics, reporting and operational data, including dimensional, 3NF, Data Vault and semantic patterns.
- Strong experience designing end-to-end data architectures on modern cloud data platforms; practical knowledge of Databricks or a comparable enterprise lakehouse platform is highly advantageous.
- Experience defining authoritative sources, system-of-record boundaries, data contracts, lineage and master/reference data approaches across multiple systems or domains.
- Strong understanding of metadata, data catalogue, data quality, privacy, security, retention and governance-by-design, with experience working alongside governance functions and tooling such as Alation.
- Experience designing data architectures that support analytics, semantic layers and reporting at enterprise scale; familiarity with Tableau, Looker or comparable technologies is beneficial.
- Experience leading architecture for data migration, platform modernisation, consolidation, application replacement or legacy retirement, including transition and reconciliation approaches.
- Proven ability to act as senior technical authority, constructively challenge architects, engineers, system integrators and vendors, and make pragmatic recommendations as requirements and technology evolve.
- Experience working across Product, Engineering, Enterprise Architecture, Integration, Security, Governance and business teams in product-led, Agile or squad-based environments.
- Experience coaching or mentoring other architects or senior technical specialists and raising the quality and consistency of architecture practice across teams.
- Strong communication and influencing skills, able to explain complex data architecture trade-offs clearly to senior technical and non-technical stakeholders and drive alignment.
- Experience with Retail, Fashion, Luxury or Consumer Goods data - particularly Product, Customer, Merchandise, Sales, Inventory and Supply Chain domains - is highly beneficial.
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