Job
Description
As a Senior Data Engineer specializing in Ontology & Knowledge Graph Systems, your primary focus will be on designing and implementing a semantic data layer that harmonizes complex data assets across various domains. You will be responsible for building Palantir-style ontology and knowledge graph systems utilizing open-source technologies to facilitate interpretability, analytics, and AI-driven workflows. Key Responsibilities: - Design and implement scalable ontology or knowledge graph models representing business and technical domains. - Construct and manage data pipelines (batch and streaming) to ingest, transform, and map heterogeneous data into semantic structures. - Develop and optimize storage and query layers utilizing graph databases or RDF/OWL frameworks such as Neo4j, Apache Jena, TerminusDB. - Integrate with APIs and orchestration systems to operationalize actions and workflows on ontology objects. - Implement and maintain SPARQL, Cypher, or GraphQL interfaces for downstream applications. - Collaborate with data scientists and AI teams to expose graph-based features for modeling and analytics. - Ensure data lineage, versioning, and governance of ontology schemas and transformations. - Establish telemetry, metrics, and automated tests for data quality and consistency. - Mentor other engineers on semantic modeling, data integration patterns, and graph-based system design. Required Skills and Experience: - 6+ years of experience in data engineering, with a solid background in distributed data systems. - Expertise in data modeling, ontology design (RDF/OWL), and graph data structures. - Proficiency with graph databases (Neo4j, TerminusDB, ArangoDB) and query languages (SPARQL, Cypher, GraphQL). - Hands-on experience with Apache Spark or similar distributed data processing frameworks. - Strong understanding of ETL/ELT workflows and data integration across multiple systems. - Proficiency in Python, Scala, or Java. - Experience in designing and managing APIs, preferably GraphQL-based data access layers. - Familiarity with workflow orchestration tools (Airflow, Temporal, Camunda) and CI/CD pipelines. - Strong knowledge of data governance, schema evolution, and version control for ontology/data models. - Excellent communication and documentation skills for collaborating with cross-functional teams. Preferred Qualifications: - Experience with semantic web technologies (RDF, OWL, SHACL). - Background in AI/ML pipelines leveraging graph or semantic data. - Understanding of reasoning and inference systems. - Experience with cloud-based data platforms (AWS, GCP, or Azure). In this role, you will play a pivotal part in establishing the foundation of our semantic data architecture, creating a unified and interpretable data layer that drives decision intelligence, analytics, and AI-driven systems throughout the organization. As a Senior Data Engineer specializing in Ontology & Knowledge Graph Systems, your primary focus will be on designing and implementing a semantic data layer that harmonizes complex data assets across various domains. You will be responsible for building Palantir-style ontology and knowledge graph systems utilizing open-source technologies to facilitate interpretability, analytics, and AI-driven workflows. Key Responsibilities: - Design and implement scalable ontology or knowledge graph models representing business and technical domains. - Construct and manage data pipelines (batch and streaming) to ingest, transform, and map heterogeneous data into semantic structures. - Develop and optimize storage and query layers utilizing graph databases or RDF/OWL frameworks such as Neo4j, Apache Jena, TerminusDB. - Integrate with APIs and orchestration systems to operationalize actions and workflows on ontology objects. - Implement and maintain SPARQL, Cypher, or GraphQL interfaces for downstream applications. - Collaborate with data scientists and AI teams to expose graph-based features for modeling and analytics. - Ensure data lineage, versioning, and governance of ontology schemas and transformations. - Establish telemetry, metrics, and automated tests for data quality and consistency. - Mentor other engineers on semantic modeling, data integration patterns, and graph-based system design. Required Skills and Experience: - 6+ years of experience in data engineering, with a solid background in distributed data systems. - Expertise in data modeling, ontology design (RDF/OWL), and graph data structures. - Proficiency with graph databases (Neo4j, TerminusDB, ArangoDB) and query languages (SPARQL, Cypher, GraphQL). - Hands-on experience with Apache Spark or similar distributed data processing frameworks. - Strong understanding of ETL/ELT workflows and data integration across multiple systems. - Proficiency in Python, Scala, or Java. - Experience in designing and managing APIs, preferably GraphQL-based data access layers. - Familiarity with workflow orchestration tools (Airflow, Temporal, Camunda) and
