DevOps Data Platform Engineer in London

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.

The Data Platform Engineer is responsible for the operational reliability and day-to-day technical administration of Burberry's core data and analytics platforms, primarily Databricks and Tableau Plus, with oversight of Alation and BigEye. The role provides hands-on technical ownership across configuration, access, monitoring, troubleshooting, release coordination, change enablement, operational readiness, documentation and continuous improvement.

For Tableau Plus, the role owns platform administration, service health, access, configuration, performance and operational support; responsibility for report content, business metrics and visualisation outputs remains with the relevant data, analytics and business teams. The Data Platform Engineer provides Burberry-side technical ownership, assurance and escalation support, ensuring the partner has the context, standards, runbooks and direction needed to support the platforms effectively.

Accountable for hands-on administration, configuration, monitoring, operational support, service assurance and continuous improvement across Databricks, Tableau Plus, Alation and BigEye. Accountable for ensuring platform processes, security controls, monitoring, change activity and operational documentation are robust, supportable and aligned to Burberry technology standards. Not accountable for enterprise data architecture, business data models, report/dashboard content, data product delivery or business-facing analytics outputs.

Key interfaces include Senior Manager, Data Platforms, Data Platform Architect, Data Engineering, Visualisation & Reporting, Data Product teams, Data Governance, Cyber Security, Cloud & Infrastructure, SIAM, Service Desk, operational support partner, MLOps/AI teams and strategic technology vendors.

Provide hands-on technical ownership for Databricks and Tableau Plus, ensuring both platforms are available, secure, performant, well-administered and fit for use by consuming teams. Provide platform oversight for Alation and BigEye, ensuring governance, catalogue, data observability and related operational processes are understood, monitored and effectively supported.

Manage platform administration activities, including workspace/site configuration, access controls, identity integration, user onboarding, environment settings, usage controls and operational configuration. Work closely with Burberry's operational support partner to ensure 24/7 incident management, monitoring, routine operational activity, escalation and service restoration processes are effective and consistently followed.

Coordinate operational change, release activity, vendor-managed upgrades, platform patches and security fixes within the constraints of SaaS operating models, ensuring appropriate communication, testing, risk assessment and change governance. Support ITIL-aligned service management processes, including incident, problem, change, release, request fulfilment, service transition and operational readiness.

Monitor platform health, including availability, performance, usage, error rates, capacity, cost trends, job reliability, dashboard performance, data observability signals and service degradation indicators. Investigate and resolve platform issues, providing L2/L3 technical support, root-cause analysis, remediation planning, vendor escalation and clear communication to affected teams.

Maintain and improve monitoring, alerting, runbooks, knowledge articles, operational procedures and support documentation so the support model is repeatable, auditable and resilient. Implement practical automation where it improves reliability, reduces manual effort or improves control, while recognising that core platform lifecycle activity may be vendor-managed in a SaaS environment.

Work with architecture, cyber security, service management and vendor teams to ensure platform standards, access models, security controls, audit logging and operational processes remain fit for purpose. Support Data Engineering, Visualisation & Reporting, Data Product and AI/MLOps teams with guidance on platform usage, support routes, good practice, performance considerations and operational constraints.

Provide operational reporting and insight on service performance, incidents, changes, usage, cost trends, capacity, risks, partner performance and improvement actions. Build strong working relationships across internal technology teams, business users, data teams, vendors and support partners to ensure issues are progressed effectively and users receive a reliable platform service.

Hands-on experience administering, supporting or operating enterprise data and analytics platforms, with strong preference for Databricks and Tableau/Tableau Plus. Good working knowledge of Databricks administration, workspace configuration, job/runtime support, access controls, performance troubleshooting, monitoring and operational support. Good working knowledge of Tableau platform administration, including site/project permissions, user access, extract refreshes, dashboard performance, operational monitoring and support processes.

Experience with data governance, catalogue or observability platforms such as Alation and BigEye is desirable. Good knowledge of ITIL-aligned service management, including incident, problem, change, release, request fulfilment, service transition and operational readiness. Experience coordinating SaaS platform releases, vendor-managed upgrades, patches, security fixes, configuration changes, testing and user communications.

Strong monitoring, troubleshooting and incident management skills, including L2/L3 support, root-cause analysis and vendor escalation. Understanding of identity and access management, role-based access control, audit logging, security configuration and operational controls for enterprise SaaS platforms. Able to work effectively with architecture, data engineering, visualisation and reporting, cyber security, cloud infrastructure, service management, business users, vendors and support partners.