Job Summary

We are looking for an experienced Data Modeler to design and govern enterprise data models for a large-scale GCP-based Unified Data Platform (UDP) in the Insurance domain. The role will drive data architecture, canonical modeling, data products, analytics, and governance initiatives across the enterprise data landscape.

Key Responsibilities

• Design and maintain conceptual, logical, and physical data models across Customer, Policy, Claims, Lead, Campaign, and Finance domains.
• Develop dimensional models, data marts, fact and dimension structures, and analytical data products.
• Define canonical, conformed, and reusable enterprise data models.
• Create and maintain source-to-target mappings, transformation rules, and data lineage documentation.
• Collaborate with Business Analysts, Architects, and Data Engineers to translate business requirements into scalable data solutions.
• Establish and enforce enterprise data modeling standards and governance practices.
• Support Bronze, Silver, Gold, and Data Product layer design and implementation.
• Conduct model reviews, impact assessments, and change analysis for source systems and reporting solutions.
• Drive data quality, metadata management, master data, and lineage initiatives.
• Support regulatory, operational, and analytical reporting requirements.
• Mentor team members on data modeling best practices.

Skill Requirements

• Strong expertise in Conceptual, Logical, and Physical Data Modeling.
• Hands-on experience with Dimensional Modeling (Kimball Methodology).
• Proficiency in ER Studio, Erwin, Lucidchart, or similar modeling tools.
• Strong understanding of Data Warehousing, Lakehouse, and Enterprise Analytics architectures.
• Experience with BigQuery, GCP Data Platforms, or cloud-based analytics solutions.
• Strong SQL and database design skills.
• Knowledge of Data Governance, Metadata Management, Data Lineage, and Data Quality frameworks.
• Experience designing canonical and conformed data models.
• Excellent stakeholder management, communication, and problem-solving skills.
• Very good at prompt engineering using AI tools. Should be able to demonstrate how business requirements can be converted to technical artifacts

Preferred Skills

• Experience in Insurance, Healthcare, or Financial Services domains.
• Knowledge of ACORD and/or FHIR data standards.
• Understanding of Customer 360, Policy, Claims, Lead, and Campaign data domains.
• Familiarity with Data Products, Data Mesh, and Modern Lakehouse architectures.
• Experience supporting enterprise-scale cloud transformation programs.

Key Competencies

• Enterprise Data Architecture
• Data Modeling & Governance
• Analytical and Problem-Solving Skills
• Stakeholder Management
• Leadership and Mentoring
• Cross-functional Collaboration
• Business-to-Data Translation

Other Requirements