We are seeking an experienced Graph Data Engineer / Knowledge Graph Specialist to design, build, and optimize scalable graph-based data solutions. The ideal candidate will have strong expertise in graph databases, ontologies, and graph analytics, along with hands-on experience in Python, Azure, Databricks, Spark, and SQL.

You will play a key role in building enterprise-grade knowledge graphs, enabling advanced data relationships, semantic modeling, and graph-driven insights.

Key Responsibilities

🔹 Graph Data Engineering

• Design, develop, and maintain graph databases (Neo4j / Stardog / AllegroGraph / TigerGraph)
• Build and optimize knowledge graphs for large-scale structured and unstructured datasets
• Model complex relationships using graph schemas and ontology frameworks

🔹 Ontologies & Semantic Modeling

• Develop and implement ontologies, taxonomies, and semantic data models
• Work with RDF, OWL, and SPARQL for semantic data representation and querying
• Ensure data consistency, governance, and semantic integrity

🔹 Data Processing & Integration

• Build scalable data pipelines using Python, PySpark, Spark, and SQL
• Ingest, transform, and integrate data from multiple sources into graph structures
• Work with Azure Data Services (Data Lake, Synapse, Databricks)

🔹 Graph Analytics & Insights

• Perform graph analytics (centrality, pathfinding, community detection, etc.)
• Develop algorithms and use cases for fraud detection, recommendation systems, entity resolution, etc.
• Enable advanced analytics and visualization of graph data

🔹 Cloud & Platform Engineering

• Deploy and manage graph solutions on Microsoft Azure
• Use Databricks for large-scale graph processing and analytics
• Optimize performance and scalability of graph workloads

🔹 Collaboration & Stakeholder Engagement

• Work with data scientists, engineers, and business teams to define requirements
• Translate complex business problems into graph-based solutions
• Provide technical guidance and best practices

Required Skills

Must-Have

• 5+ years of experience in data engineering / graph-based solutions
• Strong proficiency in Python, SQL, and Spark (PySpark)
• Hands-on experience with at least one graph database:
• Neo4j / Stardog / AllegroGraph / TigerGraph
• Experience with Microsoft Azure (Data Lake, Databricks, Synapse)
• Understanding of graph data modeling and graph theory fundamentals
• Experience with graph query languages (Cypher / SPARQL / Gremlin)

Good to Have

• Knowledge of RDF, OWL, Linked Data standards
• Experience with entity resolution / master data management
• Familiarity with data governance and metadata management tools
• Exposure to ML/AI use cases on graph data

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field

Preferred Experience

• Building enterprise-scale knowledge graphs
• Working with semantic web technologies
• Implementing graph solutions in domains like finance, retail, healthcare, or telecom

What You’ll Gain

• Opportunity to work on cutting-edge graph and semantic technologies
• Exposure to large-scale data platforms using Azure & Databricks
• Collaborative and innovation-driven work environment