Ontology SME

Antal International; Pune District; Sur place; INR 1 500 000 - 2 100 000; Plein temps

Résumé du poste

Antal International is seeking an Ontology Subject Matter Expert (SME) in Pune to design and manage semantic data models, develop knowledge graphs, and implement graph-based solutions using Python. The role focuses on ontology modeling, defining relationships, and integrating structured data into graph systems.

The candidate will work with data engineers and business stakeholders to map diverse data sources, ensure semantic accuracy, and support data integration and graph queries across

Qualifications

• Hands-on ontology engineering or knowledge graph development experience.
• Proficiency with graph databases such as Neo4j, Neptune, or similar.
• Strong Python programming for data processing and automation.

Responsabilités

• Design, develop, and maintain ontologies, taxonomies, and semantic data models.
• Define entities, attributes, relationships, and business rules for complex data.
• Develop and maintain knowledge graphs using graph databases.
• Use Python for data processing, transformation, validation, and automation.
• Map data from multiple sources to ontology models and graph structures.
• Collaborate with data engineers, architects, and stakeholders on domain requirements.
• Ensure data quality, consistency, and semantic accuracy.
• Support graph querying, troubleshooting, documentation, and optimization.

Connaissances

Ontology engineering

Knowledge graphs

Graph databases

Python

RDF/RDFS/OWL/SPARQL

Data modeling

Semantic data integration

Communication skills

Outils

Neo4j

Amazon Neptune

Protégé

RDF triple stores

Description du poste

Job Title: Ontology SME

Key Skills:

Ontology, Graph Database (Graph DB), Python

Job Summary

We are looking for an Ontology Subject Matter Expert (SME) with experience in ontology modeling, knowledge graphs, graph databases, and Python. The candidate will help design and manage semantic data models, define relationships between entities, and develop Python-based solutions to process, validate, and integrate structured data into graph-based systems.

Key Responsibilities

• Design, develop, and maintain ontologies, taxonomies, and semantic data models.
• Define entities, attributes, relationships, and business rules to represent complex data.
• Develop and maintain knowledge graphs using graph database technologies.
• Use Python for data processing, transformation, validation, and automation.
• Map data from multiple sources to ontology models and graph structures.
• Collaborate with data engineers, architects, and business stakeholders to understand domain requirements.
• Ensure data consistency, quality, reusability, and semantic accuracy.
• Support graph querying, troubleshooting, documentation, and optimization.

Required Skills

• Hands-on experience in ontology engineering, ontology modeling, or knowledge graph development.
• Experience with graph databases such as Neo4j, Amazon Neptune, or similar technologies.
• Strong Python programming skills for data processing and automation.
• Understanding of RDF, RDFS, OWL, SPARQL, or related semantic web technologies, as applicable.
• Knowledge of entity relationships, data modeling, metadata, and semantic data integration.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with ontology tools such as Protégé.
• Exposure to RDF triple stores, graph data modeling, and knowledge graph pipelines.
• Familiarity with APIs, ETL/data integration, and large-scale data processing.

Skillset Required

Skillset Required: Ontology, Graph Database, Python, Ontology modeling, Knowledge graphs, Semantic data models, Entities and relationships definition, Python-based data processing, Data validation, Data integration, Taxonomies, Semantic accuracy, Graph querying, Troubleshooting, Documentation, Optimization, Ontology engineering, Neo4j, Amazon Neptune, RDF, RDFS, OWL, SPARQL, Semantic web technologies, Entity relationships, Data modeling, Metadata, Semantic data integration, Analytical skills, Problem-solving skills, Communication skills, Protégé, RDF triple stores, Graph data modeling, Knowledge graph pipelines, APIs, ETL, Data integration, Large-scale data processing