Data Modeler

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
• Event and Integration Schema Design
• Design event payload schemas for domain events published across distributed services
• Ensure event schemas are registered and versioned in the schema registry following enterprise versioning standards
• Collaborate with integration teams to define data contracts at domain boundaries
• Documentation and Governance
• Maintain a current data dictionary and model catalog covering all active domains
• Participate in architecture and design reviews present model decisions with clear rationale
• Support data lineage documentation linking source systems, transformation logic, and consumption layers

• 5+ years of data modeling experience in complex enterprise or multi-domain environments
• Strong proficiency in logical and physical data modeling ER modeling, normalization, dimensional modeling
• Experience modeling for multiple implementation patterns: OLTP relational, dimensional warehouse, and lakehouse or medallion architectures
• Hands-on with relational databases PostgreSQL, SQL Server, or Oracle
• Proficiency in SQL writing, reviewing, and optimizing queries and DDL scripts
• Experience with data modeling tools: ERwin, draw.io, dbt, or equivalent
• Familiarity with event-driven data design and schema registries (Confluent, AWS Glue, or similar)

Collaboration and Communication :

• Ability to work directly with domain SMEs and engineers to gather requirements and validate models
• Clear communicator comfortable explaining model decisions and trade-offs in design reviews
• Detail-oriented consistent in naming, documentation, and standards application

Preferred :

• Experience in government healthcare programs such as Medicaid, CHIP, or Medicare
• Familiarity with healthcare transaction data: claims (professional, institutional, pharmacy), eligibility, provider, or enrollment
• Knowledge of healthcare data standards: X12 EDI, NCPDP, FHIR R4, or HL7
• Background in MMIS, claims processing systems, or health plan administration is a strong advantage but not required
• Experience with Python for data profiling, validation scripts, or pipeline support