Burberry Solutions Architect

BoF Careers; Greater London; On-site; GBP 120,000 - 150,000; Full time

Job summary

Burberry in London is seeking a Data Platform Architect to own the enterprise data platform architecture, ensuring performance, security and cost efficiency while aligning with enterprise standards. This role will shape architectural governance for scalable data initiatives across cross-functional squads.

You will lead ingestion and semantic layer architecture, support MLOps and advanced analytics, and collaborate with senior managers to evolve the platform roadmap, including SAP BW and

Qualifications

• Extensive Databricks and lakehouse experience with cost management and performance.
• Demonstrated ability to define architectural standards and governance.
• Experience in cloud-native architectures and CI/CD pipelines.

Responsibilities

• Design and maintain the platform's technical architecture, including compute/storage design, ingestion frameworks, access control, performance tuning, and capacity planning.
• Define and maintain architectural standards and guardrails, naming conventions, deployment pipelines, and cost optimisation patterns.
• Own platform cost modelling and FinOps governance, defining cost allocation patterns and identifying optimisation opportunities.
• Align with Data Senior Solution Architect to ensure consistency with enterprise data models.
• Translate architectural direction into practical engineering guidance for Data Platform Engineers.
• Design data ingestion architecture (batch, micro-batch, streaming) with clear boundaries for system integration.
• Define architecture for semantic layer and self-serve analytics infrastructure.
• Provide input to data squads for complex data products and support Data Engineers.
• Ensure architecture supports emerging requirements including agentic AI data infrastructure and MLOps.
• Collaborate with Senior Manager, Data Platform Engineering to align operations with target architecture.
• Own the data platform roadmap and contribute to governance forums.
• Maintain documentation of design decisions, patterns, and trade-offs.
• Define non-functional standards for resilience, DR, observability and operational readiness.

Skills

Databricks

Unity Catalog

Delta Lake

Spark

Databricks SQL

CI/CD pipelines

Cloud-native architecture

Cost models

Data security

Ingestion patterns

SAP Datasphere

Tools

SAP Datasphere

Job description

INTRODUCTION

At Burberry, we believe creativity opens spaces. Our purpose is to unlock the power of imagination to push boundaries and open new possibilities for our people, our customers and our communities. This is the core belief that has guided Burberry since it was founded in 1856 and is central to how we operate as a company today.

We aim to provide an environment for creative minds from different backgrounds to thrive, bringing a wide range of skills and experiences to everything we do. As a purposeful, values-driven brand, we are committed to being a force for good in the world as well, creating the next generation of sustainable luxury for customers, driving industry change and championing our communities.

Job Purpose

The Data Platform Architect is accountable for the technical architecture of the enterprise data platform, ensuring it meets the demands of a growing data estate while maintaining performance, cost efficiency, security, and alignment with enterprise architecture standards. This role will be expected to own the internal technical architecture (compute and storage design, ingestion framework patterns, data modelling standards, and access control architecture, platform performance and capacity planning, and establishing architectural authority, documenting design decisions, and ensuring knowledge retention within Burberry.

This role defines the architecture, sets the standards, provides design governance, and ensures what is built is consistent, scalable, and aligned to the enterprise technology strategy. The architect participates in cross‑functional squads where architectural input is required, providing design guidance for complex data initiatives.

ACCOUNTABILITY BOUNDARIES AND KEY INTERFACES

• Accountable for platform architecture, standards, technical guardrails, architectural roadmap and design assurance for the enterprise data platform.
• Not accountable for day‑to‑day platform operations or individual data product delivery, but accountable for the architectural standards those teams consume.
• Key interfaces include Enterprise Data, Enterprise Platforms & Operations, Data Governance, Cyber Security, Solution Architecture, MLOps/AI teams and strategic technology vendors.

Responsibilities

• Design and maintain the platform's technical architecture, including compute/storage design, ingestion frameworks, access control, performance tuning, and capacity planning.
• Define and maintain architectural standards and guardrails (naming conventions, environment management, deployment pipelines, partitioning strategies, and cost optimisation patterns).
• Own platform cost modelling and FinOps governance, defining cost allocation patterns and identifying optimisation opportunities.
• Align with the Data Senior Solution Architect and Data Solution Architects to ensure consistency with enterprise data architecture and models.
• Translate architectural direction into practical engineering guidance for Data Platform Engineers and Data Engineers, ensuring teams can implement within defined standards without requiring bespoke architectural intervention for standard use cases.
• Design data ingestion architecture (batch, micro‑batch, and streaming) with clear boundaries for system‑to‑system integration.
• Define architecture for the semantic layer and self‑serve analytics infrastructure.
• Provide input to data squads for complex data products and support Data Product Managers and Data Engineers where architectural complexity requires it.
• Ensure architecture supports emerging requirements, including agentic AI data infrastructure, MLOps productionisation, and advanced analytics.
• Collaborate with the Senior Manager, Data Platform Engineering (within the Enterprise Platforms & Operations team) to ensure platform operations are aligned to the target architecture, providing feedback on feasibility and translating architectural decisions into implementable guidance.
• Collaborate with the Senior Manager, Data Engineering (within the Enterprise Data team) to ensure data engineering work follows defined patterns and standards.
• Own the data platform roadmap from an architectural perspective, defining how the platform evolves over time (e.g., SAP BW transition/retirement path, Databricks maturation, Datasphere integration layer decisions).
• Contribute to enterprise architecture governance forums, representing data platform considerations in broader technology decisions.
• Provide architectural input to vendor and tooling decisions, evaluating technology options and providing recommendations for platform evolution.
• Maintain comprehensive documentation of design decisions, patterns, standards, and trade‑offs.
• Define non‑functional platform architecture standards covering resilience, backup/restore, disaster recovery, observability, service levels, auditability and operational readiness.
• Define platform security and privacy architecture in partnership with Cyber Security and Data Governance, including PII handling, access recertification, audit logging and retention patterns.
• Establish architecture decision records, exception/waiver processes and design scorecards so deviations from platform standards are visible, time‑bound and governed.
• Maintain platform adoption, performance, cost and standards‑compliance metrics, using them to guide roadmap priorities and architecture governance decisions.

PERSONAL PROFILE

• Deep expertise in Databricks (Unity Catalog, Delta Lake, Spark, Databricks SQL) or equivalent Lakehouse platforms, including administration, cost management, and performance optimisation.
• Strong understanding of cloud‑native architecture principles, cost models, and practical experience with CI/CD pipelines and environment strategies.
• Proven implementation of data security (encryption, RBAC, column/row‑level security, data masking).
• Strong understanding of ingestion and pipeline architecture patterns for diverse source systems.
• Experience with SAP data landscapes (BW, Datasphere, S/4HANA data flows) is highly desirable given the Burberry technology estate.
• Experience defining architectural standards and patterns that engineering teams implement and comfortable setting direction without hands‑on delivery.
• Experience working within a centralised architecture function that engages flexibly with delivery squads.
• Ability to communicate architectural decisions to both technical and non‑technical stakeholders.
• Experience establishing architectural authority in environments transitioning from outsourced to in‑house ownership is beneficial.
• Experience defining non‑functional requirements and architecture patterns for enterprise‑grade resilience, observability, disaster recovery, data lifecycle management and operational readiness.
• Experience using architecture decision records, design authorities, exception management and measurable standards adoption to embed architectural governance without slowing delivery.