Data Modeler
1 week ago
Location: Onsite - Woodland Hills or Los Angeles, CA
Experience: 10+ Years
Job Description
We are seeking a highly skilled Data Modeler with extensive experience in the Property & Casualty (P&C) Insurance domain. The ideal candidate will design scalable and high-performance data models, working closely with business and technical teams to support enterprise data initiatives across Snowflake, Guidewire, and legacy platforms.
Technical Skills Required
- Snowflake
- DBT
- Erwin (or equivalent data modeling tools)
- Strong SQL skills
- Deep understanding of relational & dimensional modeling
- Design and develop logical and physical data models supporting P&C insurance business processes.
- Collaborate with Business Analysts to define and document data mapping rules from Guidewire and legacy systems.
- Optimize physical models for performance, scalability, and cost-efficiency within Snowflake.
- Ensure adherence to business requirements, technical standards, and data governance guidelines.
- Work closely with developers to validate that integration and transformations align with approved models.
- Maintain version-controlled documentation for data models, mappings, and transformation logic.
- Provide support for model implementation, troubleshooting, and continuous enhancement.
- Participate in data quality assessments, model validation, and performance tuning.
- Offer guidance and training to cross-functional teams on data model interpretation and usage.
- 10+ years of experience in data modeling and data architecture roles.
- Strong background in the P&C Insurance domain with hands-on experience designing data models for systems like Guidewire.
- Expertise using tools such as Erwin for modeling.
- Strong understanding of relational, dimensional, and canonical modeling concepts.
- Proficiency in SQL and data validation techniques.
- Excellent analytical, communication, and stakeholder collaboration skills.
- Experience with Snowflake cloud data platform.
- Exposure to Guidewire and Legacy/Mainframe systems.
- Familiarity with ETL/ELT processes, metadata management, and general data governance practices.
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