Responsibilities:
Logical Data Modeling: Develop and maintain logical data models using best practices, ensuring accuracy and efficiency in the representation of complex business requirements.
Tool Proficiency: Demonstrate expertise in utilizing Snowflake and Erwin modeling tools for logical data modeling tasks, ensuring seamless collaboration and efficient workflow.
Dimensional Modeling: Design and implement dimensional models to support business intelligence and analytical reporting needs, optimizing data structures for performance and query efficiency.
Conceptual Modeling: Translate high-level business requirements into conceptual models, ensuring alignment between business objectives and data architecture.
Physical Data Model Creation: Collaborate with database administrators and engineers to translate logical and conceptual models into efficient physical data models, optimizing database performance and storage utilization.
Data Integrity: Ensure data integrity and accuracy within logical and physical data models, implementing validation techniques and data governance best practices.
Documentation: Create comprehensive documentation for all data models, including entity-relationship diagrams, data dictionaries, and metadata definitions, ensuring clear communication and understanding among stakeholders.
Collaboration: Collaborate effectively with cross-functional teams, including business analysts, developers, and architects, to gather requirements, resolve issues, and ensure the successful implementation of data models.
Requirements:
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• Proven experience in logical data modeling using Snowflake and Erwin modeling tools.
• Strong understanding of dimensional modeling, conceptual modeling, and physical data model creation.
• Proficiency in SQL and database query optimization techniques.
• Excellent analytical and problem-solving skills with attention to detail.
• Strong communication and interpersonal skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Experience working in agile environments and ability to adapt to changing requirements.
• Knowledge of data governance principles and best practices is a plus.