Data Modeller | 5 - 7 Years of Experience

Job Description :

We are looking for an experienced Data Modeller with 5 - 7 years of relevant experience in data architecture, knowledge graphs and graph databases, preferably within the healthcare domain.

The candidate will be responsible for designing scalable data models and knowledge graph solutions that support complex healthcare use cases, clinical decision support and population health analytics.

The ideal candidate should have strong hands-on expertise in graph data modelling, ontology design, graph query optimization, Knowledge Graph ETL and API integration, along with the ability to work closely with Data Scientists, Software Engineers and Health Informatics teams.

Key Responsibilities :

Knowledge Graph & Graph Database Modelling :

- Design and implement scalable Knowledge Graphs and graph database solutions for complex healthcare datasets.

- Evaluate graph engines and recommend appropriate technologies based on business, technical and scalability requirements.

- Develop graph patterns, information architectures and semantic data models.

- Design and maintain ontologies relevant to healthcare and clinical data.

- Define relationships, entities, properties and graph structures to support analytical and operational use cases.

Healthcare Data & Analytics :

- Work with complex healthcare and clinical datasets to develop effective data models.

- Design solutions supporting clinical decision support, population health analytics and healthcare intelligence.

- Collaborate with health informaticians and domain experts to translate clinical requirements into scalable graph models.

- Ensure data models accurately represent healthcare entities, relationships and business rules.

Query Design & Performance Optimization :

- Develop and optimize graph queries for performance, scalability and reliability.

- Analyze query execution and identify opportunities for optimization across large-scale graph databases.

- Understand how graph structures and modelling decisions impact algorithm efficiency and application performance.

- Translate graph-based queries and requirements into structured queries where required.

API & Application Integration :

- Design, provision and manage APIs to expose graph database capabilities to applications and downstream systems.

- Integrate graph solutions with application layers and enterprise technologies such as Spring.

- Collaborate with software engineers to ensure efficient and secure data access.

- Support API performance, scalability and integration requirements.

Graph Data Management & ETL :

- Develop and manage Knowledge Graph ETL pipelines for ingesting and transforming healthcare data.

- Perform graph data loading, validation, transformation and quality checks.

- Manage leaf-node level changes and property-level modifications within graph structures.

- Ensure consistency, accuracy and integrity of graph data.

Scalability & Architecture :

- Design graph solutions capable of handling large-scale datasets involving tens of millions of patients.

- Identify scalability and performance bottlenecks and implement appropriate solutions.

- Evaluate emerging graph technologies and recommend improvements based on evolving business and technical requirements.

- Stay updated with trends and best practices in graph databases, knowledge graphs and healthcare technology.

Required Skills & Qualifications :

- 5 - 7 years of relevant experience in Data Modelling, Data Architecture, Knowledge Graphs or Graph Databases.

- Strong hands-on experience with graph data modelling and graph database technologies.

- Knowledge of ontologies, semantic modelling and information architecture.

- Experience with graph query languages and query optimization.

- Strong understanding of healthcare/clinical data is highly preferred.

- Experience with Knowledge Graph ETL and graph data management.

- Experience designing APIs and integrating graph databases with application layers.

- Strong understanding of scalability and performance optimization for large datasets.

- Excellent analytical, problem-solving and collaboration skills.

- Ability to work effectively with Data Scientists, Software Engineers and healthcare domain experts.