Ontology & Identity: Knowledge Graph Architect

Samba; San Francisco (CA); Hybrid; USD 165,000 - 190,000; Full time

Job summary

Samba seeks a hands-on Ontologist/Data Scientist to build and extend the knowledge graph schemas, derivation pipelines, and graph data models behind our measurement and audience intelligence products. You will own scoped work streams and grow your depth in semantic modeling under the Senior Ontologist.

Responsibilities include implementing ontology schemas (RDF/RDFS/OWL), validating graphs with SHACL, building PySpark and Databricks pipelines, writing production Python code, and applying

Qualifications

• 2+ years of hands-on knowledge graph development and semantic data modeling.
• Proficient in RDF/RDFS/OWL vocabularies and graph databases.
• Strong Python, PySpark, and Databricks experience.
• Experience with entity resolution and data quality checks.

Responsibilities

• Implement ontology schemas and manage versioning.
• Build SHACL validation shapes to ensure data quality.
• Develop PySpark and Databricks pipelines for graph attributes with incremental refresh.
• Write production-ready SPARQL and Python code.
• Collaborate with data engineering, product, and operations on schema updates.

Skills

Knowledge graph development

Semantic data modeling

Ontology engineering

Python

PySpark

Databricks

Entity resolution / data matching

SPARQL

RDF/RDFS/OWL

Graph databases

Embedding models / vector search

QA / data quality awareness

Education

Bachelor's degree in Computer Science, Information Science, Mathematics, or related field

Tools

RDF

RDFS

OWL

SPARQL

Databricks

PySpark

Amazon Neptune or Stardog

Job description

Samba seeks a hands-on Ontologist/Data Scientist to build and extend the knowledge graph schemas, derivation pipelines, and graph data models behind our measurement and audience intelligence products. You will own scoped work streams and grow your depth in semantic modeling under the Senior Ontologist.

Responsibilities include implementing ontology schemas (RDF/RDFS/OWL), validating graphs with SHACL, building PySpark and Databricks pipelines, writing production Python code, and applying