Semantic Data Architect / Knowledge Architect

Triunity Software
Atlanta, United States of America
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

Atlanta, United States of America

Tech stack

Artificial Intelligence
Airflow
Architectural Patterns
Google BigQuery
Data as a Services
Data Architecture
Information Engineering
Data Governance
Distributed Systems
Data Flow Control
Graph Database
Neo4j
Resource Description Framework (RDF)
SPARQL
Google Cloud Platform
Data Classification
Data Layers
Collibra
Low Latency
Virtual Agents

Job description

We are looking for a Semantic Data Architect / Knowledge Architect to lead foundational ontology and semantic layer design for a large-scale enterprise data initiative at a major credit bureau. The focus is on formal domain modeling, knowledge graph design, and metadata governance - establishing the conceptual backbone that enables downstream AI and agentic workflows. Owns end-to-end architecture for a federated, agent-mediated semantic layer spanning 20+ distributed systems on Google Cloud Platform. The primary deliverable is a well-structured semantic model for domains such as credit, digital identity, workforce (income/ employment), auto lending, insurance, mortgage, utilities, and government.

This is not a traditional data engineering or Google Cloud Platform platform role. Hands-on role - expected to design, prototype, and validate critical architectural patterns across the knowledge graph, ontology, and agentic AI stack.

Roles and Responsibilities

  • Design and govern enterprise ontologies using RDF/OWL standards for customer credit, digital identity, workforce (income/employment), auto lending, insurance, mortgage, and utilities data

  • Define business taxonomies, semantic vocabularies, and data classification frameworks aligned to compliance requirements

  • Build and evolve knowledge graph schemas for property graph and RDF-based representations

  • Integrate semantic layer with enterprise data catalog tooling including Collibra and Google Data Catalog / Dataplex

  • Collaborate with AI architects to ensure ontology structures are optimized for agent-driven retrieval and context injection addressing concerns of latency, accuracy, explainability, and compliance

  • Work with Google Cloud Platform data services such as Spanner Graph and BigQuery to align logical models with physical graph storage

  • Lead problem framing and POC design sessions with client stakeholders to define ontology structure and graph schemas

  • Produce architecture artifacts including ontology documentation, semantic layer blueprints, and governance frameworks

  • Conduct architecture reviews, define NFRs (latency, scalability, accuracy, explainability, compliance), and establish technical guardrails

  • Mentor and guide the India-based delivery team on architecture patterns and best practices

Requirements

  • 15+ years in enterprise architecture with at least 3 years in a principal/chief architect capacity

  • Deep experience in Ontology design using OWL / RDF / RDFS,

  • Production experience designing knowledge graphs, ontologies, or semantic layers (RDF/OWL, Property Graphs, SPARQL, Cypher)

  • Experience architecting federated/distributed metadata systems and data governance

  • Experience with Collibra for data catalog, business glossary, and policy governance

  • Experience with SPARQL and / or Cypher query proficiency

  • Experience with credit bureau data models, FCRA compliance, permissible-use governance, or equivalent regulated financial data environments

  • Proven ability to operate as a client-facing technical leader in enterprise engagements

Nice-to-Have Skills

  • Direct experience with Credit Bureau technology stacks

  • Google Data Catalog / Dataplex hands-on experience

  • Google Cloud Platform Spanner Graph or Neo4j for graph storage

  • Familiarity with GraphRAG or semantic retrieval patterns

  • Experience with FIBO (Financial Industry Business Ontology)

  • Understanding of agentic AI patterns - MCP servers, LangGraph, tool orchestration, agent-mediated workflows

  • Experience with Google Cloud Platform data & AI stack: Vertex AI, BigQuery, Spanner (including Spanner Graph), Dataplex, Cloud Composer, Dataflow

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