Senior AI Analytics Engineer

YOUR IMPACT

• Build and maintain high-quality LookML models, ensuring the semantic layer is enriched with accurate labels, descriptions, synonyms, and business logic that AI tools — including Looker Conversational Analytics and external LLMs — can reliably consume;
• Design and configure domain-focused Data Agents with well-structured instructions, Golden Queries, and scoped context governance to deliver accurate and trustworthy conversational analytics;
• Develop and maintain CI/CD pipelines that automate metadata governance, including AI-assisted description generation, DDL synchronization, and semantic consistency checks;
• Build reusable AI skills, tools, and workflows that allow analysts and stakeholders to interact with governed data through natural language interfaces;
• Partner with Data Analysts, Data Engineers, and business stakeholders to translate vague or poorly defined business questions into well-defined, measurable data models and agent instructions;
• Identify opportunities to improve the quality and reliability of AI-generated insights by improving context structure, metadata coverage, and semantic layer precision;
• Develop recommendations and drive improvements to data standards, processes, and definitions;
• Contribute to cross-team guidelines and best practices for responsible AI usage with data.

WHO YOU ARE

• 3-5+ years of relevant work experience in analytics engineering, data modeling, or a closely related field;
• Excellent SQL skills required;
• Proficiency in Python — comfortable writing and maintaining production-grade scripts and automation pipelines, not just exploratory code;
• Hands-on experience with a semantic layer or BI modeling tool (LookML/Looker, dbt Sema