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 What You Bring Core Skills
- 5+ years of data modeling experience in complex enterprise or multi-domain environments
- Robust 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

📌 Data Modeler (Bengaluru)
🏢 Tech Mahindra
📍 Bengaluru