Data Platform Architect

In this role you will own the architectural direction of the enterprise data platform, aligning compute, storage, ingestion, security, and governance with the company’s transformation goals. You will collaborate with solution architects, governance, and security teams to keep the platform scalable, secure, and cost-efficient as the data estate grows. This central architecture role shapes standards and patterns across data and engineering squads, driving the platform’s maturation and future capabilities. You will influence the platform’s roadmap and ensure robust documentation and operational readiness.

• Hybrid working (4 days/week)
• Competitive pension and bonus scheme
• Genuine influence over a major enterprise data transformation

• Define and maintain the platform's technical architecture, including compute, storage, ingestion, access controls, performance tuning and capacity planning
• Set architectural standards and guardrails for naming, environments, pipelines, partitioning, and cost optimisation
• Lead platform FinOps governance and cost modelling, allocating costs and identifying optimisation opportunities
• Design data ingestion architecture across batch, micro-batch and streaming with clear system boundaries
• Define architecture for semantic layer and self-serve analytics infrastructure
• Establish non-functional standards for resilience, backup/restore, DR, observability and ops readiness
• Define security and privacy architecture with Cyber Security and Data Governance, including PII handling and audit logging
• Own the data platform roadmap and transition plans for legacy systems and platform maturation
• Represent data platform considerations in enterprise architecture governance forums
• Maintain documentation of design decisions, patterns, standards and trade-offs

• 7 to 10+ years’ experience in data platform architecture, data engineering or cloud data infrastructure
• Deep expertise in Databricks (Unity Catalog, Delta Lake, Spark, Databricks SQL) or equivalent Lakehouse platform
• Strong understanding of cloud-native architecture principles, cost models and CI/CD pipelines
• Proven experience implementing data security including encryption, RBAC, column/row level security and data masking
• Experience with SAP data landscapes is highly desirable
• Experience defining architectural standards for engineering teams and operating within a centralised architecture function
• Strong communication skills for technical and non-technical stakeholders

• strong communication
• stakeholder management
• architecture translation for diverse audiences
• Databricks (Unity Catalog, Delta Lake, Spark, Databricks SQL)
• Lakehouse architecture
• cloud-native architecture