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Specialized Snowflake+Cortex skillset plus strong employer brand in a metro raises competition to a moderate level.
Strong Snowflake/Cortex specialization plus healthcare data privacy needs make background fit highly industry-sensitive.
Explicit 6+ years, mandatory Snowflake/Cortex expertise, and healthcare compliance requirements create strict technical shortlisting filters.
Own design and delivery of end-to-end Snowflake-native ML platforms and autonomous AI agent systems for rare disease commercial analytics.
Lead technical standards, architecture, and operational excellence including production pipelines, model lifecycle, monitoring, cost optimization, and governance in Snowflake and Cortex AI environments.
Mentor engineers and collaborate with data science and commercial teams to translate complex analytics into scalable, secure, and auditable operational AI solutions.
6–10+ years experience in Data Engineering, MLOps, or ML Platform roles with proven ML solution architecture and deployment at scale.
3+ years building advanced analytics or data science solutions specifically on Snowflake with deep expertise in Snowpark, Model Registry, Containers, and performance optimization.
Strong proficiency in Cortex AI including LLM functions, fine-tuning, embedding generation, and deployment of enterprise AI applications within Snowflake.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field, or equivalent professional experience.
Senior technical leader with demonstrated ability to architect Snowflake-native ML and AI platforms minimizing external compute dependency.
Experienced in building autonomous AI agent workflows and prompt engineering within regulated, high-compliance environments like healthcare/pharma.
Hands-on experience with CI/CD, TDD, containerization, infrastructure-as-code, and secure enterprise integration supporting production-grade AI solutions.