Data Architect

Data Architect - Enterprise Data Platform About the Role We’re looking for an experienced Data Architect to help shape and modernise an enterprise data platform. This is an opportunity to influence how data is structured, integrated and managed across the organisation, supporting both analytics and operational workloads. You’ll work closely with data and engineering teams to establish scalable data architecture and improve the overall platform. Key Responsibilities • Design enterprise data models, structures and schemas. • Define how data is connected and integrated across systems. • Architect end-to-end data flows and platform integrations. • Establish scalable data warehousing and platform solutions. • Support data engineering teams with robust architectural guidance. • Improve data reliability, quality and platform performance. • Contribute to long-term data platform strategy and standards. Key Skills & Experience • Strong experience in Data Architecture and enterprise data modelling. • Strong SQL and data warehousing experience. • Hands-on understanding of ETL/ELT, data pipelines and data integration. • Experience working with modern cloud data platforms. • Experience with one or more of AWS, Azure or GCP. • Experience with platforms such as Snowflake, Redshift or BigQuery. • Familiarity with tools such as Airflow, dbt, Informatica or Azure Data Factory. • Ability to work across enterprise-level data structures rather than isolated reporting solutions. • Typically 7–15 years' experience across data architecture or data engineering. Why Join? This is a chance to join a data platform that is actively being modernised rather than simply maintained. You’ll have genuine influence over how enterprise data is structured, connected, moved and scaled, while working closely with senior data and engineering stakeholders. Ideal Candidate We’re looking for an architect who combines strategic thinking with practical data-platform experience. You should be comfortable designing enterprise-level structures and integrations while understanding the engineering realities of pipelines, warehousing and cloud data environments.