Data Modeler About the Role 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

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

Explicit 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