Data Architect
<b>Requirements:</b>
<ul><li>5 years experience in data architecture, integration architecture, or senior data engineering roles</li><li>Strong knowledge of data warehousing, dimensional modelling, and slowly changing dimensions</li><li>Experience with iPaaS and integration platforms (MDM experience highly desirable)</li><li>Exposure to cloud-based data platforms (e.g. Azure analytics services)</li><li>Experience working across enterprise data domains such as Finance, HR, and CRM</li><li>Understanding of data governance, metadata management, and GDPR principles</li><li>Comfortable working in agile environments and across multidisciplinary teams</li></ul>
<b>Responsibilities:</b>
<ul><li>Define and maintain conceptual and logical data models across operational systems, MDM, and the data warehouse</li><li>Lead the design and implementation of an enterprise Master Data Management capability</li><li>Design and govern data integrations between core systems (e.g. Finance, HR, CRM, case/matter management systems)</li><li>Own and evolve the organisations data architecture blueprint across ingestion, transformation, modelling, and consumption layers</li><li>Provide architectural oversight for data warehousing and BI semantic models</li><li>Work closely with data engineers, integration developers, BI teams, and third-party system integrators</li><li>Establish data standards, quality rules, ownership, and stewardship models</li><li>Contribute to and embed decisions agreed via a Data Governance forum</li><li>Ensure compliance with data protection, information security, and regulatory requirements</li></ul>
<b>Technologies:</b>
<ul><li>Architect</li><li>Azure</li><li>Cloud</li><li>CRM</li><li>Data Warehouse</li><li>Security</li></ul>
<p><b>More:</b></p>
<p>We are a professional services organisation seeking an experienced Data Architect to lead the design and evolution of our enterprise data landscape. This is a hands-on role within our data and architecture function, responsible for shaping integration patterns, master data management, and the data warehouse, ensuring data is trusted, well-governed, and fit for analytics and decision-making.</p>
<p>last updated 8 week of 2026</p>