EROS Technologies Inc

Data Modeler (W2 Role Only No C2C and Local Candidate)

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Modeler based in Princeton, NJ, on a contract basis. Requires strong insurance domain expertise, skills in data modeling, integration, and governance, with a focus on enterprise-level models for underwriting and claims.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
-
🗓️ - Date
April 8, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
Hybrid
-
📄 - Contract
W2 Contractor
-
🔒 - Security
Unknown
-
📍 - Location detailed
Princeton, NJ
-
🧠 - Skills detailed
#Migration #Data Quality #Physical Data Model #Data Lake #Scala #Data Engineering #Documentation #Metadata #Data Modeling #Business Analysis #Data Governance #Cloud #Data Integration #Data Warehouse
Role description
Title: Data Modeler Location: Princeton, NJ (Hybrid) Type: Contract Experienced Data Modeler with strong Insurance domain expertise to design, develop, and maintain enterprise-level data models that support underwriting, policy administration, claims, billing, and analytics initiatives. The ideal candidate will work closely with business stakeholders, architects, and engineering teams to translate complex insurance business requirements into scalable and compliant data models. Key Responsibilities: • Design and maintain conceptual, logical, and physical data models for insurance systems and data platforms. • Work closely with business analysts, underwriters, actuaries, claims, and IT teams to understand data requirements. • Model core insurance entities such as Policy, Coverage, Risk, Claim, Exposure, Party, Billing, and Reinsurance. • Support data modeling for transactional systems, data warehouses, data lakes, and analytics platforms. • Ensure data models adhere to industry standards, regulatory requirements, and data governance policies. • Define data definitions, business rules, relationships, and metadata. • Support data integration, migration, and modernization initiatives (legacy to cloud). • Review and optimize data models for performance, scalability, and data quality. • Collaborate with data engineers and developers during implementation. • Participate in design reviews, impact analysis, and documentation.