Brickendon Consulting is an award-winning global management and technology consultancy specializing in innovative solutions and transforming complex, highly regulated environments. Founded in 2010, Brickendon has a strong focus on financial services and the public sector, helping organizations navigate and implement significant changes. We have delivered projects for some of the world’s largest firms in financial services, governments, and leading fintechs and startups, including JP Morgan, HSBC, Deutsche Bank and Rolls Royce. We are currently seeking a Lead Data Architect for one of our clients. ✅ Work location: London ✅ Work setting: hybrid Key Responsibilities Design the UDM across the four domains (Customers, Applications, Assessments, Cases), aligning with the DSFS data model and existing Netezza structures. Produce the EDW logical and physical data models, dimensional models for the Semantic Layer, and Data Lake zone architecture (Bronze / Silver / Gold). Define Enterprise Semantic Layer design, including pre-computed aggregations, dimensional models, and Tableau connectivity specifications. Lead source system profiling (D02), producing profile reports for each system in the seven-system scope. Ensure data model designs meet NFRs: 200 concurrent users, 1-hour maximum response time, and 99.5% availability. Provide architectural guidance to the Data Architect and Lakehouse Data Engineers on detailed implementation. Knowledge and Experience Minimum 8 years in data architecture, with at least 3 years leading enterprise data model design. Experience designing Lakehouse architecture: medallion architecture (Bronze / Silver / Gold), Delta Lake, or equivalent. Proficiency in dimensional modelling (Kimball methodology) and enterprise data modelling. Experience with Databricks (Unity Catalog, Delta Lake) or Snowflake on AWS. Knowledge of Semantic Layer design patterns: pre-computed aggregations, business-facing views, Tableau integration. Experience migrating from legacy EDW platforms (Netezza, Teradata, Oracle) to cloud-native architectures.