Data Modeler

Data Modeler

Location: Daytona Beach, FL – Onsite

Primary Skill: Data Modeling Databricks Lakehouse Azure Data Platform

Experience in Years: 8 to 12 Years

Must Have Skills:

• Strong experience in Enterprise Data Modeling including Conceptual Logical and Physical Data Models
• Experience designing data models for Databricks Lakehouse Architecture Bronze Silver Gold layers
• Expertise in Dimensional Modeling Star Schema Snowflake Schema and Data Vault concepts
• Strong knowledge of Azure Databricks Delta Lake and Spark-based data platforms
• Experience in Source-to-Target Mapping Data Lineage and Data Quality Frameworks
• Advanced SQL and Data Analysis skills
• Experience working with large-scale Data Warehouse Data Lake and Data Modernization programs
• Ability to collaborate with Business Analysts Data Architects and Engineering teams to translate business requirements into scalable data models

Secondary Nice To Have Skills Not Mandatory:

• Azure Data Factory ADF
• Microsoft Purview
• Unity Catalog and Data Governance Frameworks
• Snowflake Data Platform
• Power BI and Semantic Modelling
• Python PySpark
• Data Mesh and Data Product Architecture
• Insurance Financial Services or Data Modernization project experience

Soft Skills:

• Strong stakeholder communication and requirement gathering skills
• Ability to conduct data discovery workshops with business users
• Excellent analytical and problem-solving capabilities
• Strong documentation and presentation skills
• Ability to work in Agile Scrum teams
• Self-driven with ownership mindset and attention to detail
• Collaboration and mentoring abilities across cross-functional teams

Key Responsibilities:

• Design and maintain conceptual logical and physical data models for enterprise data platforms
• Define data entities attributes relationships and business rules for Lakehouse implementations
• Develop Source-to-Target Mapping documents and support data migration activities
• Collaborate with Data Architects and Engineering teams to design curated Silver and Gold layer data structures
• Ensure data governance quality consistency and scalability across the platform
• Support data modernization and cloud transformation initiatives
• Participate in data model reviews architecture discussions and governance processes

Qualifying Questions:

• Can you explain a Databricks Lakehouse data model that you designed and how it supported Bronze Silver and Gold layer data curation?
• Describe a data modernization or migration project where you created source-to-target mappings and redesigned the target data model. What challenges did you encounter?
• How would you model customer policy or transaction data to support both reporting and future AIML use cases while maintaining scalability and governance?