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 Platform & Solution Design
- 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, xkybehq 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
- 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
Hands-on experience and architectural leadership across modern cloud data stacks, ideally including: