Ontology Engineer: Knowledge Graph & AI Data Pipelines

HeadHR; Poland; Remote; PLN 120,000 - 180,000; Full time

Job summary

Andersen is hiring an Ontology Engineer to build a large-scale Knowledge Graph and deliver AI-powered data solutions. You will implement RDF/RDFS/OWL schemas, create SHACL shapes, and develop PySpark pipelines to aggregate data for graph-based analytics.

The role requires hands-on experience with semantic web standards, SPARQL, and embedding-based approaches. Join a global technology provider delivering data analytics and AI-powered solutions.

Qualifications

• Implement RDF/RDFS/OWL ontology schemas in a graph database with entity classes and properties.
• Build and maintain SHACL validation shapes for post-load graph consistency checks.
• Write efficient SPARQL queries and graph traversals to support data science.
• Work with PySpark and Databricks to process high-volume data in graph pipelines.
• Apply embedding-based approaches and knowledge-graph enrichment techniques.
• Develop expertise in W3C semantic web standards and RDF-native databases.

Responsibilities

• Implementing and extending RDF/RDFS/OWL ontology schemas in the graph database - adding entity classes, properties.
• Building and maintaining SHACL validation shapes for post-load graph consistency checks.
• Contributing to the event-to-ontology transformation and derivation layer with PySpark/Databricks pipelines.
• Implementing derivation logic as specified by the Senior Ontologist and data science team.
• Writing production-quality Python - clean, tested, and reusable code.
• Working with PySpark/Databricks to process high-volume data within graph pipelines.
• Actively developing expertise in W3C semantic web standards and RDF-native graph databases.

Skills

RDF/OWL ontology

SHACL validation

SPARQL queries

Graph traversals

PySpark/Databricks

Python

semantic web standards

embedding-based approaches

Tools

Amazon Neptune

Stardog

Databricks

SPARQL toolings

Job description

Andersen is hiring an Ontology Engineer to build a large-scale Knowledge Graph and deliver AI-powered data solutions. You will implement RDF/RDFS/OWL schemas, create SHACL shapes, and develop PySpark pipelines to aggregate data for graph-based analytics.

The role requires hands-on experience with semantic web standards, SPARQL, and embedding-based approaches. Join a global technology provider delivering data analytics and AI-powered solutions.