AI & Analytics for today’s business challenges.
Ontology Architect
Location
United States
Posted
2 days ago
Salary
0
Seniority
Senior
Job Description
Ontology Architect
Tiger Analytics
- **Ontology & Taxonomy Design:** Lead the creation, modeling, and evolution of enterprise-wide ontologies, taxonomies, and controlled vocabularies that accurately represent complex business domains. - **Knowledge Graph Architecture:** Design and implement scalable architecture, ingestion pipelines, and governance for enterprise Knowledge Graphs (Triple Stores or Property Graphs). - **Semantic Layer Strategy:** Build and maintain the enterprise semantic layer to abstract physical data complexities, providing a unified, machine-readable business view of data. - **Data Product Augmentation:** Partner with domain data teams to map, link, and augment decentralized **Data Products** using the central ontology to ensure semantic interoperability across the organization. - **Inference & Reasoning:** Implement semantic reasoning and inference rules to automatically generate new metadata and uncover hidden insights within the graph. - **Governance & Standards:** Establish best practices, version control mechanisms, and data contracts for semantic models, ensuring consistent graph schema updates across business units.
Job Requirements
- Semantic Standards:** Expert-level mastery of core semantic technologies
- Knowledge Graph Engineering:** Hands-on experience designing and operating production-grade Graph Databases / Triple Stores (e.g., **GraphDB, Stardog, Amazon Neptune, AllegroGraph, or Neo4j**).
- Ontology Modeling Tools:** Proficiency with industry-standard ontology engineering and taxonomy management software (e.g., **Protégé, TopBraid Composer, PoolParty**).
- Modern Data Frameworks:** Clear, practical understanding of **Data Mesh** paradigms, specifically how to design a semantic layer that overlays federated, domain-driven **Data Products**.
- Traditional Data Modeling:** Strong baseline in classic data concepts, including relational databases, dimensional modeling, and ETL/ELT integration patterns.
- Preferred Skills
- Data Quality & Validation:** Hands-on experience to enforce data quality and constraint validation across graph structures.
- Advanced AI & Graph Analytics:** Familiarity with graph algorithms, graph machine learning (GNNs), or leveraging Knowledge Graphs to enhance Large Language Model architectures via Graph RAG (Retrieval-Aug Generation).
Benefits
- Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
- Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.***
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