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Tier-1 employer, metro location, and mid-level experience increase competition despite niche graph specialization.
Specialized graph and semantic engineering skills limit cross-industry transferability moderately.
Explicit 5+ years requirement plus specific AWS, graph, and TIMBR-like tooling mandates raise strictness.
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Design, build, and maintain graph-based data structures and knowledge graph solutions on AWS and TIMBR-like platforms to unify enterprise data context.
Develop and operationalize scalable pipelines that ingest, transform, and populate graph data from source systems, ensuring production readiness and governance.
Optimize graph performance and collaborate with architects, ontology modelers, and engineers to support applications and AI/agentic workflows relying on consistent, governed data context.
5+ years of experience in data engineering, graph engineering, semantic engineering, or related roles.
Strong hands-on experience with AWS cloud technologies.
Experience with graph databases, knowledge graphs, semantic layers, or ontology-driven models; familiarity with TIMBR or similar tools.
Work Experience Required: 5+ years; Notice Period: Not explicitly mentioned in the JD.
Experienced graph engineer comfortable designing and optimizing enterprise-scale graph models for diverse applications including AI/agentic systems.
Familiar with semantic technologies, ontologies, and agentic AI concepts, enabling collaboration across multiple teams and domains.
Able to deliver production-ready, governed, and secure graph infrastructures within a cloud-native environment, supporting complex data interoperability challenges.