Remote Ontology Data Modeler

Required Skills & Experience □ Bachelor's Degree in a technical field □ 5+ years of experience working in data modeling o Skilled in designing conceptual, logical and physical data models to accurately represent data structures o Proven track record in driving source systems, generating models, and supporting the business needs from a data perspective o Proficient with data modeling tools such as erwin Data Modeler, ER/Studio, or IBM Data Architect □ 2+ years of hands-on experience with Ontology Design and Implementation o Skilled in creating semantic data models, reasoning engines, validation rules, developing semantic metadate and tagging strategies, and maintaining knowledge graphs o Familiarity with Ontology tools like Protégé, TopBraid Composer, and FluentEditor o Proficient in Ontology languages such as OWL (Web Ontology Language), RDF (Resource Description Framework), and SHACL (Shapes Constraint Language) □ Demonstrated ability to articulate ideas clearly, effectively engage with stakeholders, and communicate the process and benefits of ontology creation Nice to Have Skills & Experience □ Hands-on experience with AWS Glue □ 3+ years of experience with Spark, Kafka or other big data processing frameworks □ Experience with Informatica, Talend or Apache NiFi □ Prior experience with AWS GovCloud, Data Catalogue or AWS RedShift Experience in the aviation industry or other regulated industries □ Strong experience in AWS Cloud, Python, and SQL Job Description A Fortune 100 client's Aviation Analytics program is seeking an Ontology Data Modeler to join their team. This individual will design and implement ontologies to accurately represent manufacturing processes, part configurations, supply chain hierarchies, logistics, quality events, and compliance frameworks. They will collaborate with domain experts across engineering, quality, logistics, and IT to formalize vocabulary and relationships using standards such as OWL, RDF, and SHACL. Additionally, they will develop and maintain knowledge graphs integrating data from MES, ERP, PLM, QMS, and IoT sources, supporting digital twin, root cause analysis, predictive quality, and sustainability efforts. The individual will implement reasoning engines and validation rules to infer product dependencies, identify anomalies, and ensure data integrity. They will be responsible for driving the development of semantic metadata and tagging strategies for advanced search, lineage tracing, and knowledge reuse, aligning ontological structures with enterprise data strategies and digital engineering initiatives, including MBSE. The ability to articulate ideas clearly, effectively engage with stakeholders, and communicate the process and benefits of ontology creation is vital for this position.