Proven experience (6+ years) working as a Data Modeler, preferably in a complex and enterprise-level environment.
Strong expertise in designing and developing Relational and Dimensional data models.
Proficiency in data modeling tools such as Erwin, ER/Studio, or similar tool.
Extensive knowledge of database concepts, SQL, and query optimization.
Experience with data warehousing concepts and methodologies, including star schemas, snowflake schemas, and slowly changing dimensions.
Familiarity with data integration and ETL processes.
Strong analytical and problem-solving skills with the ability to translate business requirements into data models.
Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts to non-technical stakeholders.
Knowledge of industry best practices, standards, and emerging trends in data modeling and data management.
Experience with cloud-based data platforms (e.g., AWS, Azure, GCP) is a plus.
Knowledge of Data Vault 2.0 design practices is a plus.
Bachelor’s degree in computer science, Information Systems, or a related field. Advanced degree is a plus.
Roles & Responsibilities
Design and develop Relational and Dimensional data models that accurately represent the structure and relationships of our data.
Collaborate with business stakeholders, data analysts, and application developers to understand data requirements and translate them into practical data models..
Develop and maintain data dictionaries, documentation, and metadata for all data models and databases.
Work closely with the Business Analysts, Data Analysts, Data Architects and Data Engineering/ETL teams to ensure the proper implementation and integration of data models into our data systems.
Participate in data governance activities, ensuring compliance with data standards, policies, and best practices.
Stay up-to-date with industry trends and advancements in data modeling techniques, tools, and technologies.
Collaborate with cross-functional teams to provide guidance and support on data-related initiatives, projects, and data-driven decision making.