Senior Knowledge Graph Construction Specialist

Fórmula Industrial; Abu Dhabi; Remote; AED 400,000 - 700,000; Full time

Benefits offered by this job

Competitive compensation

Professional development

Collaborative international team

Remote work

Job summary

Fórmula Industrial seeks a Senior Knowledge Graph Construction Specialist to design, develop, and maintain scalable knowledge graphs that capture complex relationships across diverse data sources.

Responsibilities include building ontologies, entity schemas, and semantic data structures; implementing RDF/OWL and graph pipelines; and collaborating with data engineers and stakeholders to ensure semantic integrity in a fully remote environment.

Qualifications

• Bachelor's or master's degree in a relevant field.
• Significant experience in knowledge graph construction or data integration.
• Proficiency with graph databases, RDF/OWL, and graph query languages.

Responsibilities

• Design scalable knowledge graph architectures for structured and unstructured data.
• Develop entity schemas, ontologies, and semantic data structures.
• Build automated data transformation pipelines into graph representations.
• Apply entity resolution and data deduplication techniques.
• Collaborate with data engineers and stakeholders.

Skills

Knowledge graphs

Graph data modeling

Semantic technologies

Entity modeling

NLP & information extraction

Data integration

Graph query languages

Prototyping & research

Education

Bachelor's or master's in CS/IS/DS/AI

Tools

Neo4j

Amazon Neptune

Python

SPARQL

OWL/RDF

Job description

Job Title: Senior Knowledge Graph Construction Specialist

Location: United Arab Emirates (Remote)

Employment Type: Full-Time

Work Arrangement: 100% Remote — Work From Home

Level: Senior

About the Role

We are seeking an experienced Senior Knowledge Graph Construction Specialist to design, develop, and maintain structured knowledge graphs that represent complex relationships between entities, concepts, and information sources. The successful candidate will combine knowledge representation, graph data modeling, semantic technologies, and data integration techniques to transform diverse datasets into interconnected, searchable, and reusable knowledge structures. This fully remote role requires strong technical expertise in graph technologies, ontology development, and data engineering.

Key Responsibilities

• Design and implement scalable knowledge graph architectures for structured and unstructured data.
• Develop entity schemas, graph models, ontologies, and semantic data structures.
• Identify and extract entities, relationships, attributes, and concepts from multiple information sources.
• Build automated pipelines for transforming source data into graph-based representations.
• Apply entity resolution and record linkage techniques to identify duplicate and equivalent entities.
• Define relationship types, entity hierarchies, semantic properties, and graph constraints.
• Develop and maintain ontologies, taxonomies, controlled vocabularies, and knowledge representation standards.
• Implement knowledge graph construction workflows using RDF, OWL, and property graph models where appropriate.
• Develop graph queries and data transformation logic using SPARQL, Cypher, or equivalent query languages.
• Integrate data from relational databases, APIs, documents, and external information repositories.
• Apply natural language processing and information extraction techniques to identify relevant entities and relationships.
• Validate graph completeness, consistency, accuracy, and semantic integrity.
• Implement procedures for resolving conflicting information, incomplete relationships, and inconsistent entity attributes.
• Optimize graph storage, indexing, traversal, and query performance.
• Collaborate with data engineers, machine learning specialists, architects, and business stakeholders.
• Establish data lineage, provenance tracking, version control, and knowledge graph governance procedures.
• Maintain technical documentation covering graph schemas, ontologies, data sources, transformation rules, and validation methods.
• Recommend improvements to knowledge graph quality, scalability, and interoperability.

Qualifications and Experience

• Bachelor's or master's degree in Computer Science, Information Systems, Data Science, Artificial Intelligence, Knowledge Management, or a related discipline.
• Significant professional experience in knowledge graph construction, graph data engineering, semantic technologies, or data integration.
• Strong understanding of graph theory, knowledge representation, entity modeling, and semantic relationships.
• Practical experience with graph databases such as Neo4j, Amazon Neptune, or equivalent platforms.
• Knowledge of RDF, OWL, RDFS, and ontology development principles.
• Proficiency in Python and relevant data processing or graph libraries.
• Experience with SPARQL, Cypher, or other graph query languages.
• Understanding of entity resolution, record linkage, and data deduplication methodologies.
• Familiarity with natural language processing and automated information extraction.
• Experience integrating data from relational databases, APIs, documents, and heterogeneous data sources.
• Knowledge of data governance, metadata management, data lineage, and semantic interoperability.
• Ability to evaluate graph quality, identify inconsistencies, and improve data reliability.
• Strong analytical reasoning, problem-solving, and technical documentation skills.
• Excellent communication and stakeholder collaboration abilities.
• Ability to manage complex technical projects independently in a fully remote environment.

What We Offer

• 100% remote working arrangement within the stated employment framework.
• Competitive compensation based on qualifications and professional experience.
• Opportunities to work on advanced knowledge graph and semantic data initiatives.
• Professional development and continuous learning opportunities.
• Collaborative environment with international and multidisciplinary teams.