Data Modeller

• Design, develop, and maintain conceptual, logical, and physical data models across enterprise data platforms.
• Translate business, finance, and regulatory requirements into scalable and compliant technical data structures.
• Design and validate dimensional data models, including fact and dimension models, star schemas, and snowflake schemas.
• Ensure data quality, consistency, governance, metadata management, and data lineage across Finance and Risk domains.
• Collaborate with Data Engineers, Product Owners, Architecture teams, and Data Office stakeholders to implement data models using Azure SQL Database, Azure Databricks, and Azure Data Factory.
• Review and optimize existing data models while establishing modelling standards and best practices.
• Support data ingestion, transformation, and integration activities throughout project delivery.
• Participate in technical discussions, architecture reviews, and solution assessments.

• 8+ years of experience as a Technical Data Modeller in complex enterprise environments.
• Expert-level SQL skills, including complex query development, relational database design, and performance tuning.
• Strong experience with Azure SQL Database, Azure Databricks, and Azure Data Factory.
• Extensive knowledge of financial data domains such as payments, credit, risk, regulatory reporting, and finance reporting.
• Hands‑on experience with data modelling techniques including normalization, denormalization, star schemas, snowflake schemas, fact and dimension modelling, Slowly Changing Dimensions (SCD), metadata management, and data lineage.
• Experience working in Agile environments.
• Strong communication and stakeholder management skills.
• Professional proficiency in Dutch and good command of English.

• Convert complex business and regulatory requirements into effective technical data models.
• Work independently and provide technical leadership on data modelling initiatives.
• Collaborate effectively with both business and technical stakeholders.
• Analyze, optimize, and maintain large-scale data structures.
• Identify data quality issues and implement governance best practices.
• Challenge requirements constructively and recommend robust technical solutions.
• Support enterprise data architecture and data engineering teams in delivering scalable solutions.

• Opportunity to work on complex data modelling initiatives within Finance and Risk domains.
• Exposure to modern Azure-based data platforms and technologies.
• Collaborative environment with cross‑functional teams including Data Engineering, Architecture, Product, and Governance teams.
• Hybrid work model with 2 days onsite and 3 days remote.
• Opportunity to contribute to large‑scale, high‑impact data transformation programs.
• Dynamic and technically challenging projects that promote continuous learning and professional growth.

Want to discuss this opportunity in more detail? Feel free to reach out.