Data Modeler

• Design, develop, and maintain conceptual, logical, and physical data models to support business needs and objectives across various domains.
• Collaborate with stakeholders, including business analysts, data architects, and application developers, to gather and define data requirements.
• Create and optimize database schemas and data structures to ensure data consistency, accuracy, and integrity.
• Implement best practices for data modelling, including normalization, de-normalization, and dimensional modelling, to support efficient data storage and retrieval.
• Lead the design and implementation of complex data architectures for enterprise-level systems, ensuring scalability and performance.
• Develop and maintain data dictionaries, data lineage documentation, and metadata repositories to support data governance and standardization efforts.
• Perform data mapping and data profiling to ensure data quality and consistency across systems and environments.
• Work closely with ETL developers to design data integration strategies, ensuring seamless data flow between source and target systems.
• Utilize data modelling tools such as Erwin, PowerDesigner, or similar to create, modify, and maintain data models and data flow diagrams.
• Provide guidance and mentorship to junior data modelers and data engineers, promoting best practices and methodologies.
• Ensure compliance with data governance policies, industry standards, and regulatory requirements for data management and privacy.
• Support data migration efforts by creating detailed data mapping and transformation rules between Legacy and target systems.
• Experience in modelling for various databases, including relational (SQL Server, Oracle, MySQL) and NoSQL (MongoDB, Cassandra) systems.
• Collaborate with BI and reporting teams to ensure data models support advanced analytics, reporting, and visualization needs.
• Analyze and optimize existing data models and database performance, identifying bottlenecks and making recommendations for improvement.
• Maintain detailed documentation of data models, schemas, and changes to ensure transparency and future scalability.