- Design and develop Conceptual, Logical, and Physical Data Models based on business requirements, ensuring alignment with data governance and architectural standards.

- Collaborate with business analysts, data engineers, and stakeholders to translate business needs into scalable and maintainable data structures.

- Perform data design, model design, and data profiling to ensure data quality, consistency, and integrity across multiple systems.

- Work with different modeling methodologies including :

- 3NF (Third Normal Form) for operational data stores.

- Data Vault modeling for scalable, auditable enterprise data warehouses.

- Common Data Model (CDM) for standardized data representation across applications.

- Industry domain models (e.g., finance, healthcare, retail) to ensure semantic consistency.

- Design and support implementation of Medallion Architecture (Bronze, Silver, Gold layers) in modern data platforms such as Microsoft Fabric, Azure Synapse, or Databricks.

- Define and maintain metrics and attributes for analytical models and ensure proper dimensional modeling for BI and reporting solutions.

- Support forward and reverse engineering processes to generate physical databases from logical models and derive models from existing databases.

- Collaborate with development teams to ensure model changes are properly implemented and version-controlled.

- Participate in performance tuning and optimization of database structures.

- Maintain documentation and metadata for all data models, ensuring compliance with data governance and architectural best practices.

Technical Skills Required :

- Strong expertise in Conceptual, Logical, and Physical Data Modeling.

- Hands-on experience in Data Design, Data Profiling, and Normalization/Denormalization techniques.

- Practical knowledge of Data Vault, 3NF, and Dimensional Modeling.

- Good understanding of Medallion Architecture (Bronze, Silver, Gold Layers) and its role in data pipelines.

- Familiarity with Common Data Model (CDM) and Industry Domain Models.

- Understanding of Forward Engineering (creating databases from models) and Reverse Engineering (deriving models from existing databases).

- Experience with at least one Data Modeling Tool such as Erwin Data Modeler, PowerDesigner, or SQL Data Modeler.

- Basic to intermediate proficiency in Erwin Data Modeler, including schema generation, version control, and metadata management.

- Familiarity with relational databases (e.g., Oracle, SQL Server, PostgreSQL) and cloud-based data platforms (e.g., Azure Synapse, MS Fabric, Snowflake).