• Evaluate and pilot semantic-layer, knowledge-graph, retrieval, and AI-agent technologies to make data more discoverable, trustworthy, and usable.
• Build working pilots, connect existing semantic layers, and provide clear build-versus-adopt recommendations.
• Onboard data domains onto the selected approach, expanding semantic content and creating reusable implementation playbooks.
• Develop AI rules, skills, files, and integrations through code or configuration to support people and AI agents.
• Partner across teams to align definitions, communicate trade-offs and risks, and drive platform adoption.

• Strong experience building semantic layers, knowledge graphs, retrieval systems, or AI/agent tooling.
• Strong SQL and Python skills with experience working in a data science environment.
• Experience with semantic-layer technologies/specifications such as MetricFlow or Open Semantic Interchange, plus MCP servers, agent orchestration, or retrieval systems.
• Working Git proficiency and experience driving adoption of data/AI capabilities across multiple teams.

LI-RP5

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