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Low — senior (8+ yrs) niche analytics-engineering role with Snowflake semantic/LLM specialization in Bangalore.
Medium — strong analytics-engineering skills transfer across industries, but semantic-layer and Cortex experience increase specialization.
High — explicit 8+ years and narrow Snowflake/semantic-layer, LLM, and analytics-engineering skill requirements.
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Design and maintain governed Snowflake Semantic Views as a shared vocabulary layer for AI agents to answer business questions.
Develop and execute evaluation mechanisms for semantic and agentic layers including test datasets and LLM-as-a-judge scoring to gate releases.
Deliver dynamic data applications and partner with BI analysts and governance teams to cross-train domain teams and ensure data quality and certification compliance.
8+ years of experience in analytics or data engineering with at least 1 year building semantic models or LLM-grounded analytics.
Deep expertise in SQL, dimensional/semantic modeling, and hands-on experience with Snowflake Semantic Views or similar semantic layers.
Strong programming skills in Python along with familiarity with Snowflake dynamic tables, streams, tasks, Snowpark, Git workflows, CI/CD, and automated testing.
Work Experience Required: 8+ years in analytics or data engineering including semantic modeling experience. Notice period: Not explicitly mentioned in the JD.
Experienced in building and shipping reusable data products that support multiple teams leveraging semantic layers.
Highly skilled in applying LLM evaluation frameworks and driving iterative improvements to AI-driven analytics.
Able to collaborate closely with BI analysts and data governance teams to operationalize semantic models and embed data quality and compliance.