Data Architect (6-Month Contract)
Key Responsibilities
Data Architecture
· Design, develop, and maintain enterprise data architecture solutions aligned with business and technology strategies
· Define and implement data models, data standards, and governance frameworks across multiple business domains
· Design scalable and secure data platforms leveraging Microsoft Azure services and Databricks
· Develop and maintain data warehouse, data lake, and lakehouse architectures to support reporting, analytics, and AI initiatives
· Establish best practices for data integration, transformation, storage, and lifecycle management
· Support cloud-based data migration and modernisation initiatives
Stakeholder Engagement and Technical Leadership
· Provide architectural guidance to data engineers, developers, analysts, and project teams
· Collaborate with business and technical teams to define data roadmaps and priorities
· Support knowledge transfer and mentoring activities across the wider technology team
Project Delivery and Governance
· Deliver data architecture initiatives using structured project management and governance methodologies
· Define solution architectures, technical specifications, and implementation roadmaps
· Identify project risks, dependencies, and mitigation strategies
· Support procurement, vendor engagement, and solution evaluation activities where required
· Ensure all architectural documentation is maintained and aligned with governance standards
Required
· A relevant third-level degree in Computer Science, Information Systems, Data Engineering, or a related discipline
· Minimum 7 years’ experience in Data Architecture, Data Engineering, or Enterprise Data Management roles
· Strong experience designing and implementing enterprise-scale data architectures
· Extensive hands-on experience with Microsoft Azure data services including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and related technologies
· Strong experience working with Databricks for data engineering, transformation, and analytics workloads
· Proven experience designing and managing enterprise data warehouse, data lake, and lakehouse solutions
· Strong understanding of data modelling techniques, including conceptual, logical, and physical data models
· Knowledge of data governance, data quality, metadata management, and security best practices
· Strong analytical and problem-solving capability
