Backend Knowledge Graph Engineer

Accenture; Detroit (MI); Hybrid; USD 39,000 - 117,000; Full time

Job summary

Accenture is seeking a Back-End Engineer to design, build, and operate the data infrastructure powering its AI-driven knowledge platform. You will work across the full back-end stack, architecting APIs, building data pipelines, and owning reliable, scalable services for product teams.

You will hydrate data into Knowledge Graphs, implement ontology mappings, and optimize graph queries and ETL workflows. This role requires hands-on experience with RDF/SPARQL, vector databases, and cloud deployment

Qualifications

• Minimum 3 years in Knowledge Graph data hydration and ontology-based data mapping.
• Experience with RDF, SPARQL, and semantic technologies.
• Hands-on experience with graph databases and SQL proficiency.
• Experience deploying and operating vector databases in production.

Responsibilities

• Hydrate data into Knowledge Graphs by mapping sources to ontology models.
• Develop data mapping and transformation workflows using R2RML or similar.
• Write and optimize SPARQL queries for graph loading, validation, and retrieval.
• Build data ingestion pipelines and integrate data from enterprise systems.
• Design and optimize relational schemas and queries to support graph hydration and ETL.
• Deploy and maintain vector database infrastructure for embedding storage and semantic retrieval.
• Design scalable graph query APIs for internal teams and ensure performance tuning.

Skills

Knowledge Graphs

SPARQL

R2RML

Python

Java

PostgreSQL

Graph databases

REST APIs

Vector databases

Data pipelines

Education

Bachelor's degree

Tools

Docker

Kubernetes

Neo4j

Elasticsearch/OpenSearch

Vector storage tech

Job description

Accenture is seeking a Back-End Engineer to design, build, and operate the data infrastructure powering its AI-driven knowledge platform. You will work across the full back-end stack, architecting APIs, building data pipelines, and owning reliable, scalable services for product teams.

You will hydrate data into Knowledge Graphs, implement ontology mappings, and optimize graph queries and ETL workflows. This role requires hands-on experience with RDF/SPARQL, vector databases, and cloud deployment