Enterprise Data Architect

We are seeking an experienced Enterprise Data Architect to join a major transformation programme within a complex enterprise environment. You will be responsible for defining and delivering the organisation’s data architecture strategy, enabling improved decision-making, operational efficiency, and governance across key business functions including Finance, Procurement, HR, Property, and Asset Management.

Working closely with Enterprise Architecture and Data & AI teams, you will design scalable data models, integration patterns, and governance frameworks that support the full asset lifecycle and future business growth.

• Design end-to-end data architecture across the asset lifecycle from planning through to retirement.
• Define current and future-state data architectures, including gap analysis and roadmaps.
• Establish authoritative data sources and data ownership across corporate functions.
• Develop enterprise data models to support integration, workflow automation, and business insight.
• Design integration architectures and event-driven data flows across business systems.
• Lead data governance initiatives including data quality, stewardship, and master data management.
• Support the development of trusted reporting and analytics data products.
• Ensure compliance with data privacy, retention, security, and regulatory requirements.
• Produce clear documentation of data models, interfaces, and data flows.
• Enable self-service reporting and improved access to high-quality business data.
• Collaborate with business stakeholders, architects, and technical teams to align data strategy with organisational objectives.

• Strong experience delivering enterprise-scale data architecture.
• Expertise in conceptual, logical, and physical data modelling.
• Experience with Oracle ERP, SQL databases, and Lakehouse platforms such as Databricks.
• Knowledge of cloud data platforms including Azure, AWS, or Google Cloud.
• Strong understanding of data governance, data quality, and master data management.
• Experience designing data integrations, APIs, and data pipelines.
• Knowledge of data security, privacy, retention, and compliance requirements.
• Experience solving complex data migration, consolidation, and integration challenges.
• Excellent stakeholder management and communication skills.
• Experience enabling analytics, reporting, and self-service data capabilities.
• Understanding of emerging technologies including AI, machine learning, real-time analytics, and data lakes.

• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Exposure to advanced analytics and machine learning solutions.
• Relevant certifications such as CDMP, Azure Data Engineer, or AWS Data Analytics.
• Experience working within large-scale infrastructure, asset-intensive, or highly regulated environments.