Overview
As a Knowledge Graph Engineer in Accenture's Data & AI practice, you will lead the architecture and delivery of semantic data solutions across industries, spanning AWS and Azure. You will shape domain models, ontologies, and scalable KG solutions, guiding teams from design to production. You’ll collaborate with clients and stakeholders to articulate value, drive end-to-end delivery, and push innovation through cutting-edge graph methods.
Compensaciones / Beneficios
Private medical, life, and accident insurance
Medical services and wellbeing programs
Versátil benefits program
Learning and career development paths
Sustainability initiatives and Accenture Foundation participation
Profit-sharing programs
Responsabilidades
Lead development of Knowledge Graph solutions within a program scope
Design, build, and deploy AI and semantic solutions ensuring cohesive integration
Collaborate with project leaders and clients to create graph-powered data offerings
Develop client relationships and earn stakeholder trust




Articulate business value of semantic layer solutions to clients
Contribute to Accenture sales and pre-sales efforts
Provide thought leadership on technology trends, opportunities, and risks
Requisitos principales
Bachelor's degree or equivalent, plus at least 3 of the following: production deployments in data/AI/Software engineering
Strong knowledge of relational DBs, object stores, graph databases (Stardog, Neo4J, Amazon Neptune, Azure Cosmos DB, Allegro Graph)
Proficiency in SPARQL and/or Gremlin/Cypher
Hands-on with at least two graph DB platforms across RDF and property graph paradigms
Experience integrating graph layers with enterprise governance platforms (Collibra, Informatica, Apache Atlas, Alation)
Cloud data architecture on AWS and/or Azure
Strong Python skills with TensorFlow/PyTorch, ETL tools (NiFi, Airflow), and advanced SQL
Experience in ontology management, KG curation, and KG-based ML models
End-to-end data pipeline design for AI apps (incl

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