Data Modeler

Day 1st Onsite

Data Modeler

Location: Chicago, IL

6+ months contract

Experience Required:

• 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 & Responsibility:

• 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.

Last updated on Nov 16, 2023