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Senior niche role but strong employer brand and metro location increase applicant interest.
Highly domain-specific skills (Knowledge Graphs, RDF, structured content workflows) limit cross-industry transferability.
Explicit 8+ years plus mandatory semantic, modeling, and production AI expertise raises filter strictness.
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Lead design and governance of scalable data models and semantic frameworks for high-volume data processing and AI-enabled workflows within Data Operations.
Provide technical leadership for Knowledge Graph and semantic data modeling initiatives, ensuring integration into operational workflows and alignment with business requirements.
Drive technical specification, workflow optimization, and cross-functional collaboration to enable production-ready, governed, and interoperable structured data ecosystems.
Bachelor’s or Master’s degree in Computer Science, Information Systems, Data Engineering, or related field.
8–12+ years of experience in data modeling, structured data processing, semantic modeling, or large-scale data operations.
Mandatory technical skills include advanced SQL, XML schema (XSD), JSON schema development, Linked Data/RDF principles, Knowledge Graph concepts, and data normalization.
Experience operationalizing AI or LLM-driven solutions in production data environments preferred; work experience requirement explicitly mentioned; notice period not explicitly mentioned.
Senior technical leader with demonstrated success leading large-scale structured data and semantic modeling projects, especially involving Knowledge Graphs and AI integration.
Strong strategic and governance mindset focused on operational resilience, workflow optimization, and cross-functional advisory roles within fast-growing data platform teams.
Experience with end-to-end workflow architecture, technical specification leadership, and practical application of GenAI/LLM technologies in data ecosystems.