Head of data architecture

Data Architecture Strategy

• Define and evolve a future-state data architecture aligned to business and technology strategy
• Establish clear architectural principles, standards, and guardrails for data platforms and products
• Strengthen governance across data modelling, metadata, lineage, and data quality

• Oversee the design of secure, resilient, and scalable data platforms including data lakes, warehouses, and streaming solutions
• Drive standardisation of cloud platforms, tooling, and integration patterns
• Reduce complexity by modernising legacy environments and addressing technical debt

• Lead, mentor, and grow a high-performing team of data architects and data modelling specialists
• Build organisational capability across data architecture, engineering, and data products
• Contribute to hiring, coaching, and long-term skills development
• Ensure data architectures meet privacy, security, and regulatory requirements (e.g. GDPR)
• Embed appropriate access controls, data security patterns, and ethical data practices
• Monitor data usage, integrity, and platform compliance
• Evaluate and adopt emerging data and analytics technologies (e.g. streaming, lakehouse, AI/ML enablement, data mesh concepts)
• Lead architectural design for a modern enterprise data platform that enables reuse, scale, and faster delivery
• Support cloud migration and enterprise modernisation initiatives

• Partner with business leaders to understand data needs and translate them into practical architectural solutions
• Work closely with engineering, analytics, and product teams to enable efficient delivery
• Communicate complex architectural concepts clearly to both technical and non-technical audiences

• Proven experience leading data architecture in a complex enterprise environment
• Previous experience managing and developing small teams of senior specialists
• Strong background in relational data platforms, SQL, and ETL / ELT patterns
• Solid understanding of core data principles (e.g. transactional vs analytical workloads)
• Experience with event-driven or streaming architectures is advantageous

Hands-on experience and architectural leadership across modern cloud data stacks, ideally including:

• Cloud data platforms and storage solutions
• Streaming and messaging technologies (e.g. Kafka or equivalent)
• Enterprise data warehouses (e.g. Snowflake or similar)
• BI and analytics platforms
• SQL-based platforms and cloud-native databases
• Integration of platforms within a secure, zero-trust hybrid cloud environment