Semantic Data Modeler

Semantic Data Modeler is responsible for designing, developing, and managing semantic data models, ontologies, taxonomies, and knowledge graph solutions to support healthcare data intelligence using graph databases, AI, and cloud platforms., * Serve as a subject matter expert in semantic data modeling on the graph data team, contributing to initiatives that integrate AI, LLMs, and advanced graph technologies.

• Collaborate with senior engineers and architects to standardize tooling, design patterns, semantic models, and modeling approaches.
• Help define the technical direction for core semantic modeling capabilities, ensuring scalable and robust solutions.
• Independently research, evaluate, and propose innovative solutions to complex and ambiguous data modeling challenges.
• Build and manage scalable knowledge graph solutions, including data ingestion, linking, and querying mechanisms.
• Write, test, and document clean, maintainable code, and apply automation to testing, integration, and deployment processes.
• Partner with product owners to refine features into actionable user stories that deliver business value.
• Evaluate and recommend external taxonomies and ontologies; author new ones as needed to support the domain.
• Recommend and implement semantic modeling tools, platforms, and technologies.
• Support ontology governance processes and enterprise graph management tools.
• Collaborate with stakeholders, including data scientists, engineers, and business teams, to understand requirements and build effective semantic solutions.
• Provide technical mentorship to junior team members on semantic data modeling principles and implementation patterns.

• Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
• Technical certification in multiple technologies is desirable.

Skills: -

Mandatory skills

• Min 8+ years of hands-on experience in semantic data modeling or knowledge graph engineering, including leading complex projects.
• Proven experience with graph databases or triple stores such as Amazon Neptune, Neo4j, Virtuoso, or GraphDB.
• Practical experience with RDF, OWL, SPARQL, and ideally SHACL.
• Experience with relational databases (SQL) and graph databases (SPARQL).
• Hands-on experience with ontology/graph tools such as Prot g , TopBraid, or Metaphactory.
• Solid understanding of data modeling, ETL processes, and data governance.
• Experience evaluating, creating, and managing taxonomies and ontologies.

Good to Have Skills

• AWS Amazon Neptune.
• Metaphactory.
• Familiarity with other languages (e.g., Java, C#, Clojure).
• Understanding of healthcare ontologies and standards like SNOMED-CT, LOINC, RxNorm, and ICD-10.
• Exposure to AI, LLMs, and advanced graph technologies.
• Experience supporting ontology governance and enterprise graph management platforms.