{"schemaVersion":"jobsearcher.job.v1","id":"db74619ef931bb4f77d68a47","url":"https://jobsearcher.com/jobs/db74619ef931bb4f77d68a47","canonicalUrl":"https://jobsearcher.com/jobs/db74619ef931bb4f77d68a47","title":"Knowledge Engineer Manager - Back-end Engineer","description":"Back-End EngineerWe are looking for a Back-End Engineer to design, build, and operate the data infrastructure and services that power our AI-driven knowledge platform. You will work across the full back-end stack — architecting APIs, building data pipelines, managing multi-modal database systems, and owning the reliability and performance of the services that application and product teams depend on. You bring strong engineering fundamentals and are equally comfortable designing a relational schema, tuning a graph query, standing up a vector store, or shipping a production-grade REST API. Knowledge graph and semantic technology experience is central to this role, but the work extends across the broader data and service layer: ingestion, transformation, storage, retrieval, and delivery at enterprise scale.Key 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 and maintain scalable graph query APIs consumed by internal application and product teams.Performance-tune graph database queries, indexing strategies, and data access 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 Technology Stack:Semantic technologies: RDF, OWL, SKOS, RDFSQuery languages: SPARQLMapping technologies: R2RML, CSVW, SHACL (preferred)Graph databases: GraphDB, Stardog, Neo4j, Amazon NeptuneRelational databases: PostgreSQL, MySQL, SQL ServerVector stores: Pinecone, Weaviate, Milvus, QdrantSearch: Elasticsearch / OpenSearchProgramming: Python, Java (preferred)Data formats: SQL, JSON, XML, CSVIntegration: REST APIs, ETL tools, Apache NiFi, Airflow (preferred)Infrastructure: Docker, Kubernetes, HelmCloud: AWS Neptune, Azure Cosmos DB, GCPMessaging: Kafka, RabbitMQVersion control: GitThis role is hybrid in nature and will require time in office and traveling to client locations. Travel can be between 20-80%.Here's What You Need:Minimum 5 years experience in Knowledge Graph data hydration and ontology-based data mapping, including strong understanding of 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 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. (If Associate's Degree, must have minimum 6 years work experience)Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.","company":"Hackajob","rawCompany":"hackajob","city":"Seattle","state":"WA","isRemote":false,"isActive":false,"createdAt":"2026-09-11T04:19:51.263Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1243.00","title":"Database Architects","slug":"database-architects"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Knowledge Engineer Manager - Back-end Engineer","description":"Back-End EngineerWe are looking for a Back-End Engineer to design, build, and operate the data infrastructure and services that power our AI-driven knowledge platform. You will work across the full back-end stack — architecting APIs, building data pipelines, managing multi-modal database systems, and owning the reliability and performance of the services that application and product teams depend on. You bring strong engineering fundamentals and are equally comfortable designing a relational schema, tuning a graph query, standing up a vector store, or shipping a production-grade REST API. Knowledge graph and semantic technology experience is central to this role, but the work extends across the broader data and service layer: ingestion, transformation, storage, retrieval, and delivery at enterprise scale.Key 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 and maintain scalable graph query APIs consumed by internal application and product teams.Performance-tune graph database queries, indexing strategies, and data access 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 Technology Stack:Semantic technologies: RDF, OWL, SKOS, RDFSQuery languages: SPARQLMapping technologies: R2RML, CSVW, SHACL (preferred)Graph databases: GraphDB, Stardog, Neo4j, Amazon NeptuneRelational databases: PostgreSQL, MySQL, SQL ServerVector stores: Pinecone, Weaviate, Milvus, QdrantSearch: Elasticsearch / OpenSearchProgramming: Python, Java (preferred)Data formats: SQL, JSON, XML, CSVIntegration: REST APIs, ETL tools, Apache NiFi, Airflow (preferred)Infrastructure: Docker, Kubernetes, HelmCloud: AWS Neptune, Azure Cosmos DB, GCPMessaging: Kafka, RabbitMQVersion control: GitThis role is hybrid in nature and will require time in office and traveling to client locations. Travel can be between 20-80%.Here's What You Need:Minimum 5 years experience in Knowledge Graph data hydration and ontology-based data mapping, including strong understanding of 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 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. (If Associate's Degree, must have minimum 6 years work experience)Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.","datePosted":"2026-09-11T04:19:51.263Z","dateModified":"2026-09-11T04:19:51.263Z","hiringOrganization":{"@type":"Organization","name":"Hackajob","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Seattle","addressRegion":"WA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"db74619ef931bb4f77d68a47"},"url":"https://jobsearcher.com/jobs/db74619ef931bb4f77d68a47"}}