Knowledge Engineer Back End Accenture San Diego
Overview
Design and build data infrastructure for AI-driven knowledge platform. Lead hydration of structured and semi-structured data into Knowledge Graphs. Develop R2RML workflows and SPARQL queries. Manage relational schemas and graph query APIs. Deploy vector databases for semantic retrieval. Ensure data quality and collaborate with ontologists.
What You'll Do11
- 1Hydrate structured and semi-structured data into Knowledge Graphs by mapping source data to ontology models
- 2Develop data mapping and transformation workflows using R2RML or similar technologies
- 3Write and optimize SPARQL queries for graph loading validation and retrieval
- 4Build and maintain data ingestion pipelines integrating enterprise systems
- 5Design and optimize relational database schemas supporting efficient graph hydration and ETL workflows
- 6Deploy containerized graph services in cloud environments with monitoring
- 7Design and maintain scalable graph query APIs for internal consumption
- 8Performance-tune graph database queries indexing strategies and data access patterns
- 9Own ownership of backend stack including API architecture and service deployment
- 10Ensure data quality ontology alignment and secure handling of PII/PHI
- 11Collaborate with ontologists architects and application teams for KG implementations
Requirements14
- 1Minimum 3 years experience in Knowledge Graph data hydration and ontology-based mapping
- 2Minimum 3 years experience with R2RML or similar frameworks
- 3Minimum 3 years experience with graph databases such as StarDog GraphWise Neo4J and Elasticsearch/OpenSearch
- 4Minimum 3 years hands-on experience with relational databases including schema design indexing and query optimization
- 5Minimum 3 years experience deploying vector databases in production environments
- 6Minimum 3 years proficiency in Python or Java for automation and REST API development
- 7Bachelor's degree or equivalent with 12 years work experience
- 8Familiarity with containerization tools Docker Kubernetes
- 9Knowledge of data ingestion pipelines ETL integration and enterprise system integration
- 10Understanding of PII/PHI handling data anonymization and governance
- 11Ability to design user-facing dashboards and applications surfacing KG data
- 12Experience with REST and GraphQL APIs BFF or API gateway patterns
- 13Familiarity with federated knowledge graph architectures and event-driven architectures
- 14Cloud platform experience with AWS Neptune Azure Cosmos DB or GCP
Salary Insight
$58 - $196k per year
Location
Required Skills
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