Back
Strong Tier-1 brand and metro mid-level role, but niche graph/semantic skillset reduces applicant density.
Specialized graph and semantic tooling skills transferable, but require ontology and platform experience.
Mandatory 5+ years, specific graph/semantic and AWS expertise required.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, build, and maintain graph-based data structures and pipelines on AWS or TIMBR-like platforms to support enterprise data context services.
Collaborate with ontology modelers, data engineers, and architects to ensure graph models align with enterprise semantics and standards.
Ensure graph data supports downstream applications and AI/agentic workflows with reliable, governed, and performant context services.
5+ years experience in data engineering, graph engineering, semantic engineering, or related roles.
Strong hands-on experience with AWS cloud technologies.
Experience working with graph databases, knowledge graphs, and TIMBR or TIMBR-like ontology-driven data access platforms.
Familiarity with agentic AI, prompt engineering, and context engineering concepts.
Technically strong graph engineer with hands-on skills in graph modeling, semantic technologies, and cloud-native data platforms.
Experienced in collaborating across data engineering, ontology modeling, and architecture teams for enterprise data context initiatives.
Able to operationalize graph infrastructure that supports AI-enabled and context-driven enterprise applications.