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Tier-1 brand and metro location increase competition, but niche knowledge-graph requirements moderate applicant density.
Specialized knowledge-graph, ontology, and semantic pipeline skills produce high industry-specific fit and lower transferability.
Explicit 7+ years requirement plus mandatory knowledge-graph, semantic, and pipeline expertise enforces strict screening.
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Lead the design and implementation of scalable data pipelines for enterprise knowledge graph and semantic context layer population.
Establish and enforce technical standards for data ingestion, transformation, validation, and synchronization ensuring production readiness and operational support.
Collaborate with ontology, architecture, and platform teams to maintain alignment with semantic standards and support AI/agentic workflows through reliable context provisioning.
7+ years of experience in data engineering, pipeline engineering, or related technical architecture roles.
Strong expertise in building scalable data pipelines and integration workflows with knowledge of knowledge graphs, ontologies, RDF, OWL, semantic enrichment, and entity modeling.
Working knowledge of agentic AI, prompt engineering, and context engineering concepts.
No relocation, visa sponsorship, or travel required; role based in Hyderabad.
Experienced technical leader in semantic data engineering focused on pipeline architecture for knowledge graph population and context serving.
Comfortable working at the intersection of data engineering, semantic web technologies, and AI-enablement to deliver enterprise context solutions.
Skilled in establishing maintainable, versioned, and observable pipelines aligned with enterprise standards and operational requirements.