[Hiring] Senior Technical Project Manager/Ontologist @RTX

Role Description

As a Technical Business Analyst, Ontology & Semantic Data Modeling, you will help establish the foundation for enterprise analytics, automation, and AI by designing scalable domain ontologies and semantic layers that provide shared, trusted meaning across RTX corporate functions. Reporting to the Associate Director of Data and AI, you will leverage enterprise systems and business knowledge to connect data across multiple functions, enabling employees and AI systems to discover, understand, and consistently interpret enterprise data.

You will collaborate with ontologists, data engineers, data stewards, AI teams, and functional experts across Finance, Supply Chain, Risk, Business Solutions, and HR to develop trusted data solutions that support enterprise decision-making and AI initiatives.

• Design scalable functional ontologies that model core business concepts, including parts, programs, suppliers, contracts, assets, employees, and cost centers, along with their relationships, properties, and business rules.
• Develop and maintain semantic layers by mapping ontology concepts to enterprise source systems, including SAP, Databricks, Snowflake, ERP, PLM, MES, HR, and Finance platforms.
• Enable trusted AI solutions by developing knowledge graphs, taxonomies, and metadata that support large language models (LLMs), retrieval-augmented generation (RAG), and agent-based applications.
• Establish ontology modeling standards, including naming conventions, version control, change management, and quality checks, while reviewing models developed by other teams.
• Partner with business functions and subject matter experts to facilitate workshops, capture business definitions and rules, and resolve conflicting definitions across functional organizations.
• Support enterprise data governance initiatives by partnering with data stewards on business glossaries, data lineage, classification, and access policies, including export-controlled data requirements such as ITAR/EAR where applicable.
• Measure ontology coverage and adoption, evaluating how semantic layers improve data reuse, consistency, and AI accuracy.
• Drive change and adoption by influencing stakeholders, building cross-functional alignment, and helping business teams understand the value of enterprise ontology and semantic data solutions.
• Manage multiple initiatives and priorities while ensuring disciplined execution, effective communication, and delivery against established timelines and objectives.
• Develop and support team members and business champions through coaching, knowledge sharing, and enablement activities.

Qualifications

• Typically requires a University Degree or equivalent experience and a minimum of 10 years of prior relevant experience, or an Advanced Degree in a related field and a minimum of 7 years of experience.
• A minimum of 5 years of hands-on experience in ontology engineering, knowledge graphs, or semantic data modeling.
• Experience with relational and dimensional data modeling, including SQL skills for profiling and mapping source data.
• Experience translating complex or ambiguous business terminology into precise, reusable data definitions.

Requirements

• Master of Science degree in Analytics.
• Strong communication skills, with the ability to effectively communicate with technical and non-technical audiences and facilitate workshops with subject matter experts.
• Strong knowledge of semantic web standards, including RDF, RDFS, OWL, SKOS, SHACL, and SPARQL.
• Experience in aerospace, defense, or complex manufacturing environments, particularly with product structures, bills of materials, configuration management, or supply chain data.
• Hands-on experience with graph databases and platforms such as Kobai, GraphDB, or Amazon Neptune.
• Experience with semantic layers and metrics stores, including dbt Semantic Layer, AtScale, Databricks Unity Catalog metrics, or Snowflake semantic views.
• Experience using knowledge graphs to ground large language models through GraphRAG, entity linking, or ontology-guided extraction.
• Python programming experience for automating ontology pipelines using tools such as rdflib or owlready2.
• Experience creating and delivering enterprise data products.
• Demonstrated ability to lead change, influence stakeholders without direct authority, and build alignment across cross-functional teams.
• Experience using data-driven insights to identify opportunities, measure adoption, and develop improvement plans.

Benefits

• Robust total rewards package with compensation.
• Healthcare, wellness, retirement and work/life benefits.
• Career development and recognition programs.
• Parental (including paternal) leave.
• Flexible work schedules.
• Achievement awards.
• Educational assistance.
• Child/adult backup care.