We are seeking a highly skilled Data Engineer with expertise in ontology development and knowledge graph implementation. You will be pivotal in shaping our data infrastructure, ensuring the accurate representation and integration of complex datasets. This role requires you to design, develop, and maintain ontologies, semantic and syntactic data models, and knowledge graphs on the Databricks Data Intelligence Platform to drive data-driven decision-making and innovation.
Roles & Responsibilities:
- Design and implement ontologies based on BFO (Basic Formal Ontology) and CCO (Common Core Ontologies) principles, ensuring alignment with business requirements and industry standards.
- Collaborate with domain experts to capture and formalize domain knowledge into ontological structures.
- Develop and maintain comprehensive ontologies to model various business entities, relationships, and processes.
- Design and implement semantic and syntactic data models that adhere to ontological principles, ensuring they are scalable, flexible, and adaptable.
- Integrate data models with existing data infrastructure and applications.
- Design and build knowledge graphs based on ontologies and data models.
- Develop algorithms and tools for knowledge graph population, enrichment, and maintenance.
- Utilize knowledge graphs to enable advanced analytics, search, and recommendation systems.
- Ensure the quality, accuracy, and consistency of ontologies, data models, and knowledge graphs.
- Define and implement data governance processes and standards for ontology development and maintenance.
- Work closely with data scientists, software engineers, and business stakeholders to understand their data requirements and provide tailored solutions.
- Communicate complex technical concepts clearly and effectively to diverse audiences.
Skills Required:
- Proven experience in ontology development using BFO and CCO or similar ontological frameworks.
- Strong knowledge of semantic web technologies, including RDF, OWL, SPARQL, and SHACL.
- Proficiency in Python, SQL, and other programming languages used for data engineering.
- Experience with graph databases (e.g., TigerGraph, JanusGraph) and triple stores (e.g., GraphDB, Stardog) is a plus.
- Familiarity with machine learning and natural language processing techniques is a plus.
- Experience with cloud-based data platforms (e.g., AWS, Azure, GCP) is a plus.
- Experience with Databricks technologies including Spark, Delta Lake, Iceberg, Unity Catalog, UniForm, and Photon is a plus.
- Strong problem-solving and analytical skills.
- Excellent communication and interpersonal skills.
QUALIFICATION:
- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
