Data Engineer - Ontology Engineering Zorba Consulting

5.0 - 7.0 years

6 - 11 Lacs

surat, gujarat, india

On-site

Role Responsibilities: Ontology Development: Design and implement ontologies based on BFO (Basic Formal Ontology) and CCO (Common Core Ontology) principles, ensuring alignment with business needs and industry standards. Collaborate with domain experts to capture and formalize domain knowledge into structured ontologies. Develop and maintain comprehensive ontologies to represent business entities, relationships, and processes. Data Modeling: Design semantic and syntactic data models adhering to ontological principles. Create scalable, flexible, and adaptable data models that meet evolving business requirements. Integrate data models with existing data infrastructures and applications. Knowledge Graph Implementation: Design and build knowledge graphs leveraging ontologies and data models. Develop algorithms and tools for knowledge graph population, enrichment, and ongoing maintenance. Utilize knowledge graphs for advanced analytics, search, and recommendation systems. Data Quality and Governance: Ensure accuracy, quality, and consistency of ontologies, data models, and knowledge graphs. Define and implement governance processes and standards for ontology and knowledge graph maintenance. Collaboration and Communication: Work closely with data scientists, software engineers, and business stakeholders to understand data requirements and provide tailored solutions. Communicate complex technical concepts clearly and effectively across diverse audiences. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Experience: 5+ years in data engineering or related roles. Proven experience with ontology development using BFO, CCO, or similar frameworks. Strong knowledge of semantic web technologies: RDF, OWL, SPARQL, SHACL. Proficiency in Python, SQL, and other relevant programming languages. Experience with graph databases (TigerGraph, JanusGraph) and triple stores (GraphDB, Stardog) is a plus. Desired Skills: Familiarity with machine learning and natural language processing (NLP) techniques. Experience with cloud platforms such as AWS, Azure, or GCP. Knowledge of Databricks technologies: Spark, Delta Lake, Iceberg, Unity Catalog, UniForm, Photon. Strong analytical and problem-solving skills. Excellent communication and interpersonal skills.

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