Tiger Analytics
Ontology Architect
US
•
Full TimeRemotePosted Today
Full TimeSeniorRemote
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Job Description
Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants br
Key Highlights
- 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.
Qualifications
Required Qualifications
- 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 Qualifications
- 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).
Skills & Technologies
Machine Learning
About the Company
Tiger Analytics
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Job Details
Employment Type
Full Time
Experience Level
Senior
Location
US • Full Time
Work Mode
Remote
Posted
Today