Data Modeler

Your responsibilities

• Design and develop conceptual, logical, and physical data models to support data warehousing initiatives specific to insurance operations.
• Collaborate with business analysts, architects, and IT teams to understand insurance business requirements and translate them into data models.
• Perform system analysis to identify, analyze, and extract the right data from source systems, ensuring data models are populated with accurate and relevant data.
• Ensure data models are optimized for performance, scalability, and maintainability, with a focus on insurance data such as policy, claims, underwriting, and customer data.
• Implement data modeling standards and best practices tailored to the insurance industry.
• Conduct data analysis and profiling to understand data quality and integrity, particularly in the context of insurance data.
• Conduct testing to validate data models, ensuring they meet business requirements and performance criteria. This includes verifying data accuracy, consistency, and integrity within the data warehousing environment.
• Work with ETL developers to ensure data models are accurately implemented in data warehousing solutions.
• Maintain and update data models as insurance business requirements evolve.
• Document data models and metadata for reference and training purposes.
• Participate in data governance and data management activities to ensure compliance with organizational policies and industry regulations.

Our requirements

• Bachelor’s degree in Computer Science, Information Systems, or a related field. Master’s degree preferred.
• Proven experience in data modeling and data warehousing, with a minimum of 2 years in a similar role, preferably within the insurance industry.
• Strong understanding of data modeling techniques, including normalization, denormalization, star schema, and snowflake schema.
• Experience with data modeling tools such as ERwin, Sparx Enterprise Architect, or similar.
• Proficiency in SQL and database management systems (e.g., SQL Server, Oracle).
• Familiarity with ETL processes and tools (e.g., Azure Data Factory, Informatica, Talend).
• Knowledge of data governance and data quality principles.
• Excellent analytical and problem-solving skills, with the ability to perform system analysis to identify and extract relevant data.
• Experience in developing and executing test plans to validate data models.
• Strong communication skills, with the ability to explain complex data concepts to non-technical stakeholders.
• Domain knowledge in insurance, including familiarity with policy administration systems, claims processing, underwriting, and regulatory requirements.
• Experience with cloud-based data solutions (e.g., Azure, AWS).
• Experience with data visualization tools (e.g., Power BI, Tableau).