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Tier-1 employer, metro location and mid-level seniority increase competition though skills are niche.
Highly specialized Snowflake+Cortex AI platform and regulated healthcare context reduces cross-industry transferability.
Explicit 6+ years, mandatory Snowflake expertise and MLOps platform skills enforce strict technical filters.
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Lead architecture and deployment of Snowflake-native ML platforms integrating Cortex AI for patient identification, predictive analytics, and commercial insights in rare disease healthcare.
Engineer, operate, and optimize scalable data pipelines, model lifecycle management, and autonomous AI agents ensuring reliability, cost-efficiency, and compliance within Snowflake ecosystem.
Provide technical leadership, mentorship, design standards, and cross-team enablement to translate analytics needs into production-grade operational systems.
6+ years in Data Engineering, MLOps, or ML Platform roles with significant experience designing and deploying ML solutions at scale.
3+ years of hands-on experience building advanced analytics or data science solutions specifically on Snowflake.
Bachelor's or Master's degree in Computer Science, Data Engineering, or related field (or equivalent professional experience).
Proficiency in Snowflake platform including Snowpark, Containers, Model Registry, and Cortex AI; strong programming skills in Python and SQL.
Experienced in architecting Snowflake-native ML and AI platforms minimizing external compute dependencies and optimizing cost-performance tradeoffs.
Deep knowledge of Cortex AI agent frameworks, prompt engineering, and building autonomous workflows relevant to regulated healthcare datasets.
Capable technical leader adept at mentoring engineers, defining standards, and collaborating with cross-functional commercial and scientific teams in fast-paced environments.