Snowflake Data Engineer

EXL • Pittsburgh, PA

3h

About The Position

We are seeking a highly skilled Snowflake Data Engineer to support healthcare data modernization by architecting, building, and scaling next-generation data and AI solutions on Snowflake. The role emphasizes Snowflake Cortex AI, intelligent agents, Streamlit applications, Snowpark analytics, data engineering, governance, and security.

The engineer will develop Cortex-powered solutions and AI agents for healthcare data, create interactive Streamlit applications, and build scalable data transformations and ELT pipelines. The role also includes optimizing Snowflake performance, implementing healthcare data architectures, integrating data sources and BI platforms, and applying governance controls and HIPAA/PHI handling practices.

The position collaborates with data scientists, ML engineers, clinical analysts, and business stakeholders, and serves as an internal Snowflake subject matter expert. It also contributes to platform roadmap planning, best practices, team onboarding, and adoption of Snowflake capabilities.

Requirements

• At least 5 years of data engineering experience, including at least 3 years of hands-on Snowflake expertise.
• Proven experience with Snowflake Cortex AI features, including LLM functions, Cortex Analyst, Cortex Search, and AI agent orchestration.
• Hands-on experience building Streamlit in Snowflake applications deployed in production environments.
• Proficiency in Snowpark for Python, including custom UDFs and UDTFs, stored procedures, and DataFrame API usage.
• Strong SQL skills and deep understanding of Snowflake's execution engine, query profiling, and optimization techniques.
• Experience with Snowflake data sharing, Marketplace, and cross-cloud or cross-region replication.
• Familiarity with vector search, embeddings, and RAG architecture patterns within or integrated with Snowflake.
• Strong understanding of analytics data modeling, including star schema, Data Vault, and Medallion/Lakehouse patterns.

Nice To Haves

• Experience with cloud platforms such as Azure and GCP, including connecting Snowflake to cloud-native services.
• Knowledge of Medicare Stars Patient Safety.

Responsibilities

• Design and deploy healthcare AI solutions using Snowflake Cortex LLM functions, including COMPLETE, SUMMARIZE, SENTIMENT, TRANSLATE, and CLASSIFY.
• Build and orchestrate multi-step AI agents using Snowflake Cortex Agents and Cortex Analyst for workflow automation and natural-language querying of structured healthcare datasets.
• Use Cortex Search for semantic and hybrid search across unstructured clinical and operational data.
• Implement RAG pipelines using Snowflake-native vector embeddings and the VECTOR data type.
• Use Arctic Embed and other Snowflake-native embedding models to build scalable AI features within Snowflake.
• Build production-grade data applications and internal tools using Streamlit in Snowflake.
• Develop self-service analytics dashboards and AI-assisted exploration tools embedded in Snowflake.
• Create Streamlit front ends that let clinical users and analysts interact with Cortex-powered outputs.
• Develop data transformations, feature engineering pipelines, and ML preprocessing workflows using Snowpark for Python.
• Build and manage scalable ELT pipelines using Snowflake Streams, Tasks, Dynamic Tables, and Snowpipe for real-time and batch ingestion.
• Optimize Snowflake performance using micro-partition pruning, clustering keys, materialized views, search optimization, and warehouse right-sizing.
• Design and implement Data Vault or Medallion architecture patterns for healthcare data platforms.
• Integrate Snowflake with upstream healthcare data sources and downstream BI platforms.
• Implement Snowflake-native governance controls, including row-level security, column masking policies, object tagging, and data classification.
• Ensure HIPAA compliance and PHI data handling best practices across Snowflake data assets.
• Manage data lineage, cataloging, and access control in alignment with organizational governance frameworks.
• Partner with data scientists, ML engineers, clinical analysts, and business stakeholders to translate requirements into Snowflake-native solutions.
• Serve as a Snowflake subject matter expert and internal champion by driving best practices, onboarding teams, and promoting platform capabilities.
• Participate in platform roadmap planning and contribute to Snowflake feature adoption strategy.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed