Ontology Specialist - Data & AI in Bangalore, भारत
Unison Group
HybridMix of office and remote
Bangalore, भारत
Role Overview
We are seeking an experienced Ontology Specialist to build the semantic foundation of an enterprise Data & AI ecosystem. The role involves designing and implementing enterprise ontologies, knowledge graphs, and reusable semantic models to connect fragmented data across product engineering, manufacturing, supply chain, operations, and commercial functions.
The specialist will collaborate with business stakeholders, enterprise architects, data engineering teams, and AI professionals to develop contextual, governed, and AI-ready data assets that enable advanced analytics, intelligent decision-making, digital twins, recommendation systems, and enterprise AI solutions.
Key Responsibilities
Design, develop, and implement enterprise ontologies and knowledge graphs across product engineering, manufacturing, supply chain, and operations domains.
Define graph schemas, taxonomies, controlled vocabularies, and semantic models aligned with enterprise lakehouse platforms, Power BI, AI/ML pipelines, and business applications.
Integrate structured, semi-structured, and unstructured data using Python, Spark/PySpark, SQL, and data orchestration pipelines.
Develop and optimize graph queries and analytics using SPARQL, Cypher, Gremlin, and KQL graph semantics.
Optimize graph performance through effective indexing, partitioning, caching, and query tuning.
Integrate knowledge graphs with Azure OpenAI, Microsoft Copilot, and agentic AI frameworks to enable GraphRAG, hybrid retrieval, semantic grounding, and explainable AI outcomes.
Establish ontology lifecycle governance, including semantic consistency, metadata management, data lineage, stewardship, versioning, and change control.
Collaborate with domain experts, business stakeholders, data architects, and AI teams to translate business requirements into scalable semantic solutions.
Serve as a technical subject matter expert for ontology engineering, knowledge graphs, and enterprise semantic architecture initiatives.
Required Qualifications
Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, Engineering, or a related discipline.
8+ years of experience in data engineering, data architecture, or related technical roles.
At least 3 years of hands-on experience in enterprise ontology engineering, knowledge graphs, or semantic architecture.
Strong expertise in semantic web technologies, including RDF/RDFS, OWL, SPARQL, SHACL, and SKOS.
Experience with ontology modeling tools such as Protégé or equivalent platforms.
Hands-on experience with Neo4j or similar graph database platforms.
Proficiency in graph query languages, including Cypher, Gremlin, and SPARQL, along with graph performance optimization techniques.
Practical experience with enterprise lakehouse/data lake architectures and Azure data services or Microsoft Fabric.
Strong programming and data processing skills in Python, PySpark, and SQL.
Experience implementing GraphRAG, vector databases, hybrid retrieval, and knowledge graph integration with Azure OpenAI or other LLM-based platforms.
Strong analytical, problem-solving, communication, and stakeholder collaboration skills.
Preferred Qualifications
Experience with Stardog, Ontotext, or equivalent ontology and knowledge graph platforms.
Familiarity with Data Mesh architectures and enterprise semantic-layer implementations.
Experience working with manufacturing, automotive, aerospace, industrial products, or engineering data.
Understanding of digital twins, AI-driven analytics, and enterprise knowledge management.
Experience delivering scalable semantic solutions across complex enterprise data ecosystems.
... graphs with Azure OpenAI, Copilot and agentic AI frameworks to support semantic grounding, GraphRAG, hybrid retrieval and explainable AI outcomes. · Establish ontology lifecycle governance covering semantic consistency, metadata, lineage, stewardship, versioning and change control in partnership with domain experts. · Act ...
... sales lifecycle, helping customers identify the right solutions while enabling our Sales teams to develop and win high-value opportunities. As a Solution Specialist - Data & AI you will act as a trusted advisor to customers and a strategic partner to our Sales teams. You will work across complex customer opportunities, ...
... enterprise context. Responsibilities Ontology Design & Maintenance: Design, develop, and maintain ontologies (using OWL/RDF or similar) that model key enterprise data domains and relationships, ensuring a consistent and shared data vocabulary across the organization. This includes collaborating with domain experts to capture ...
... ontology or knowledge graph specialist. It is a Semantic Data Architect who connects enterprise data modelling, semantic architecture, knowledge graphs, metadata governance and AI-ready data foundations to make enterprise knowledge usable by analytics, search and AI systems. What we look for - Architect by mindset, with ...
... 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 ...
... processing, application performance, and platform https://jobeax.com/link/9eklEPvZdmBNkqyh AIP Development : - Build and deploy AI-powered applications using Palantir AIP.- Develop AIP Logic workflows, AI agents, and LLM-powered applications.- Integrate enterprise data with LLMs through the Foundry Ontology.- Implement AI-driven ...
... deliverables end to end. Estimate effort, manage priorities, report progress and risks, and work independently within the agreed architecture and platform guardrails. - Work closely with Data Analysts, Data Scientists, Snowflake Developers, Data Engineers, Power BI/Fabric Developers, platform specialists and domain experts. ...
... https://jobeax.com/link/7euyNlgdp3nHCz6U Responsibilities :- Develop and maintain data pipelines, datasets, and workflows using Palantir Foundry/DataFoundry.- Work on Foundry Ontology, including data modeling, objects, relationships, and business logic.- Develop and implement solutions using Palantir AIP, including AI-enabled workflows, applications, ...
... use case AI fine-tuning strategy • Own the strategy for when we fine-tune, when we use retrieval, and when prompting is enough, based on cost, accuracy, and maintenance trade-offs • Define dataset curation standards for domain-specific training data, including labeling, provenance, and the data-handling constraints (retention, ...
... ongoing operations and upkeep. The work model for the role is: #LI Onsite, #LI Hybrid This role is contributing to the ABB Business in Bangalore. You will be mainly accountable for: - Oversee the entire process of delivering analytics solutions-starting from problem identification and data analysis to model creation and ...
... predictive DQ risk capabilities. Partnership, Governance & Adoption - Partner with Digital, IT and Data & Analytics on architecture, security, data access and future AI initiatives. - Ensure AI solutions comply with Responsible AI, data privacy, security and audit requirements. - Champion AI adoption – train and upskill MDM teams ...