Knowledge Graph Platform Lead

Accenture; Detroit (MI); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Accenture in the United States seeks a Back-End Engineer to design, build, and operate the data infrastructure powering our AI‑driven knowledge platform. You’ll work across the full back‑end stack, architecting APIs, building data pipelines, and own the reliability and performance for internal teams.

You’ll handle relational schemas, graph queries, vector stores, and production‑grade REST APIs, with knowledge graph and semantic tech at the core, extending across data ingestion, transformation,

Qualifications

• Minimum 5 years experience in Knowledge Graph data hydration and ontology‑based data mapping, including RDF, SPARQL, and semantic technologies.
• Minimum 5 years experience with R2RML or similar mapping frameworks for transforming relational data into graph models.
• Minimum 5 years experience with graph databases (e.g., StarDog, GraphWise, Neo4J), along with Elasticsearch/OpenSearch. including strong SQL proficiency.
• Minimum 5 years hands‑on experience with relational databases (e.g., PostgreSQL, MySQL, or SQL Server), including schema design, indexing, and query optimization.
• Minimum 5 years experience deploying and operating vector databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) in production environments.
• Minimum 5 years Proficiency in Python or Java for automation, integration, and service development and experience designing and documenting REST APIs for internal consumers.
• Bachelor’s degree or equivalent (minimum 12 years) work experience.

Responsibilities

• Hydrate structured and semi‑structured data into Knowledge Graphs by mapping source data to ontology models.
• Develop data mapping and transformation workflows using R2RML or similar technologies.
• Write and optimize SPARQL queries for graph loading, validation, and retrieval.
• Build and maintain data ingestion pipelines and integrate data from enterprise systems.
• Design and optimize relational database schemas and queries to support efficient graph hydration and ETL workflows.
• Deploy, configure, and maintain vector database infrastructure for embedding storage, indexing, and semantic retrieval at scale.
• Design and maintain scalable graph query APIs consumed by internal application and product teams.
• Performance‑tune graph database queries, indexing strategies, and data access patterns.
• Own containerization, deployment, and monitoring of graph services in cloud environments.
• Ensure data quality, ontology alignment, and secure handling of sensitive data (PII/PHI).
• Collaborate with ontologists, architects, and application teams to support Knowledge Graph implementations.

Skills

Knowledge Graph

RDF/SPARQL

Python/Java

REST APIs

Data pipelines

Schema design

Graph databases

ETL

Education

Bachelor’s degree or equivalent (12 yrs)

Tools

GraphDB

Stardog

Neo4j

Elasticsearch/OpenSearch

PostgreSQL/MySQL/SQL Server

Pinecone/Weaviate/Milvus/Qdrant

Docker/Kubernetes/Helm

NiFi/Airflow

AWS/Azure/GCP

Job description

Accenture in the United States seeks a Back-End Engineer to design, build, and operate the data infrastructure powering our AI‑driven knowledge platform. You’ll work across the full back‑end stack, architecting APIs, building data pipelines, and own the reliability and performance for internal teams.

You’ll handle relational schemas, graph queries, vector stores, and production‑grade REST APIs, with knowledge graph and semantic tech at the core, extending across data ingestion, transformation,