About The Role
The Data Architect / Modeler works closely with business stakeholders, data owners, and application teams to translate business and data requirements into clear, implementable target-state data models and designs on Databricks. This role bridges business understanding and technical execution — ensuring data architecture is consistent, scalable, and aligned with enterprise data strategy.
Key Responsibilities
Define and maintain conceptual, logical, and physical data models aligned with Databricks lakehouse architecture
Translate business requirements, data definitions, and business rules into structured data models and implementable designs
Analyze existing source systems, data structures, relationships, and dependencies to inform target-state architecture
Design data models leveraging Databricks Unity Catalog, Delta Lake, and medallion architecture patterns
Define and apply data architecture standards, patterns, and reusable approaches across delivery programmes
Work closely with engineering teams to ensure data models are technically feasible and implementable on Databricks
Identify and resolve data architecture and modelling gaps across business domains
Support data standardization, metadata management, lineage, and data quality considerations in target designs
Maintain traceability between business requirements and resulting target data structures
Provide hands-on guidance to delivery teams and contribute to continuous improvement of data architecture practices
Required Qualifications
5+ years hands-on experience in data architecture and data modelling
Strong experience translating business requirements into logical and physical data models
Hands-on experience with Databricks platform — Delta Lake, Unity Catalog, medallion architecture patterns
Experience with data architecture standards, patterns, and enterprise data design principles
Proficiency with data modelling tools and notation (ERD, UML, dimensional modelling)
Experience with data governance, metadata management, and data lineage
Strong communication skills with technical and business audiences
Bachelor’s degree in Computer Science, Engineering, or related field
Good to Have:
Experience designing and implementing data models on Databricks lakehouse platforms
Expertise with Delta Lake optimization, partitioning strategies, and performance tuning
Experience with Databricks SQL, Spark SQL, and data transformation on Databricks
Complex banking data and financial services data models
Large-scale data transformation or migration programmes on cloud platforms
Experience with dimensional modelling, normalized schema design, or data vault methodology
Familiarity with data quality frameworks and data lineage tools (e.g., OpenMetadata)
Experience with Agile delivery and iterative data architecture design
Master’s degree or advanced certifications in data architecture