Data Modeller

We are looking for a skilled Data Modeler to design, build, and maintain the data models that power a large government healthcare technology platform. This is a hands-on delivery role you will translate domain concepts and business requirements into precise logical and physical data models across a portfolio of products that process claims, enrollments, provider information, pharmacy transactions, and financial settlements at scale

.You will collaborate closely with data architects, engineers, and domain SMEs to ensure every data structure is well-defined, consistently named, properly classified, and ready for implementation

What You Will Do

Data Model Design and Delivery

• Design logical and physical data models for new and evolving product domains — from initial concept through implementation-ready schema
• Translate business requirements and domain concepts into entity-relationship models, normalized schemas, and dimensional structures
• Maintain models across all layers: conceptual, logical, physical, and analytics consumption
• Produce and keep current model documentation: entity definitions, attribute descriptions, data types, constraints, and relationships

Healthcare Transaction Data Modeling

• Model high-volume transactional data structures for claims processing, eligibility, enrollment, provider data, pharmacy transactions, and financial settlements
• Design reference data models: code sets, fee schedules, edit tables, and lookup structures that support point-in-time versioning and audit
• Model financial structures: accumulator records, payment details, adjustment cycles, and reconciliation outputs

Canonical and Cross-Domain Alignment

• Work within the enterprise canonical model framework to ensure implementation-level schemas align with the authoritative entity definitions for members, providers, claims, benefits, and financials
• Identify and resolve entity duplication and definitional drift across product domains
• Participate in canonical model reviews and contribute proposed additions or refinements

Data Quality and Standards Compliance

• Apply enterprise naming conventions, normalization standards, and data classification rules consistently across all models
• Tag PHI and PII fields accurately in every model in compliance with HIPAA requirements
• Validate model changes against data quality rules before promotion to production schemas