India Knowledge engineer semantic web technologies Jobs – 113 Open Jobs Today

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- Up to ₹1,00,000 a month
- Full-time
- Hybrid work
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- Master's degree
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Quick apply
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- Weekend availability
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Quick apply
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Erasmith —Delhi, Delhi
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Quick apply
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- Full-time
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Fanatics —Hyderabad, Telangana
- Full-time
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Knowledge Graph Architect - Bangalore/ Chennai/Madurai (10+ Years)
Informica Solutions —Bengaluru, Karnataka
- Full-time
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Quick apply

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Knowledge Graph Engineer

Siemens -
Pune, Maharashtra

Apply Now

Job details

Permanent | Full-time

Qualifications

Ontology
Azure
Computer Science
Relational databases
Software deployment
Information Systems
SPARQL
Taxonomy
Master's degree
Databases
SQL
AWS
Bachelor's degree
Neo4j
RDF
Semantic Web
Linked data
APIs
Data science
Metadata
AI
Graph databases
Python
Data Science

Full job description

Title : Knowledge Graph Engineer

Position Summary

We are building a connected enterprise knowledge layer that unifies structured and unstructured data across business systems and enables intelligent search, contextual retrieval, semantic reasoning, and AI-driven workflows. In this role, you will design and implement scalable knowledge graph solutions that model business entities, relationships, and domain logic to support advanced analytics, semantic applications, and next-generation AI use cases. This is a hands-on engineering role spanning graph modeling, ontology development, semantic enrichment, and enterprise data integration.

How You’ll Make an Impact (Responsibilities of Role)

Knowledge Graph Design & Engineering

Design scalable knowledge graph schemas using property graph and/or RDF-based models.
Develop and optimize graph queries using Cypher, SPARQL, or Gremlin.
Model business entities, relationships, hierarchies, and context across domains.
Build ingestion pipelines to transform enterprise data into graph structures.

Semantic Modeling & Ontology Development

Create and maintain ontologies, taxonomies, and semantic models.
Define canonical entity models and semantic mappings across data sources.
Establish semantic validation, consistency standards, and data quality checks.
Support ontology lifecycle management and schema evolution.

Data Integration & Semantic Enrichment

Collaborate with engineering teams to ingest, transform, and enrich enterprise data.
Support entity resolution, metadata enrichment, and relationship extraction.
Enable semantic search, intelligent assistants, and knowledge-driven workflows.

APIs, Collaboration & Platform Enablement

Design and support graph APIs and semantic access layers.
Partner with product, architecture, security, and domain teams on graph solutions.
Document graph modeling standards, patterns, and best practices.

Quality, Governance & Performance

Optimize query performance, indexing, and traversal efficiency.
Contribute to metadata, lineage, governance, and access control practices.
Ensure graph solutions are scalable, secure, and aligned with enterprise data standards.

What You Bring (Required Qualifications and Skill Sets)

Bachelor’s/master’s degree in computer science, Data Science, Engineering, Information Systems, Mathematics, or a related field.
5–7 years of experience in knowledge graph engineering, graph databases, semantic modeling, ontology engineering, or related data architecture roles.
Strong hands-on experience with at least one graph platform such as Neo4j, AWS Neptune, Stardog, TigerGraph, GraphDB, or similar technologies.
Proficiency in graph query languages such as Cypher, SPARQL, or Gremlin.
Experience designing graph schemas, semantic data models, taxonomies, and ontology-aligned structures for enterprise use cases.
Good understanding of knowledge graphs, RDF, OWL, semantic web concepts, ontology design, and linked data principles.
Experience integrating enterprise data from sources such as relational databases, APIs, document repositories, cloud platforms, and business applications.
Strong skills in Python and SQL for data transformation, graph ingestion, enrichment, and query support.
Familiarity with data governance, metadata management, lineage, access control, and enterprise data quality practices.
Ability to work cross-functionally with engineers, architects, business stakeholders, and domain experts to translate business concepts into scalable graph models.

Preferred Qualifications

Experience with ontology tools such as Protégé and semantic validation frameworks such as SHACL or similar approaches.
Exposure to inference, reasoning engines, rule-based modeling, or semantic constraint design.
Experience building enterprise knowledge graphs for semantic search, AI copilots, document intelligence, workflow automation, or recommendation engines.
Familiarity with vector search, RAG, hybrid graph + AI architectures, or semantic retrieval patterns.
Exposure to cloud environments such as AWS, Azure, or GCP in support of graph deployment and enterprise integration.
Understanding of observability, graph query tuning, and semantic layer performance monitoring is a plus.

Apply Now

Refine Your Search

knowledge engineer semantic web technologies jobs in india

Knowledge Graph Engineer

QA Engineer

Web Solutions Engineer, Technology and Insights Partnership Systems

Graph Engineer, Data Context Layer

Senior Full Stack Engineer (.NET, Angular, Blazor)

Design Technologist I, Design & Brand Innovation Lab

Senior Software Engineer - Knowland

SAP BW/HANA Engineer

Agentic AI Developer

Application Developer - Graph Database AI Developer- 9214

Senior AI Engineer - LLM Evaluation

Custom Software Engineer

Semantic AI/ML Architect

Lead Full Stack Engineer (UI)

Oracle AI Engineer

Staff Software Engineer

Full Stack Gen AI Engineer

AI Engineer

Staff Software Engineer

Knowledge Graph Architect - Bangalore/ Chennai/Madurai (10+ Years)

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