

Mainz Brady Group
Sr Data Engineer, Agentic AI
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Sr Data Engineer focused on Snowflake and semantic modeling within a healthcare payer environment. Contract length is "unknown," with a pay rate of "unknown." Key skills include Snowflake SQL, semantic modeling, and healthcare experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
June 13, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Portland, Oregon Metropolitan Area
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🧠 - Skills detailed
#Data Engineering #dbt (data build tool) #Datasets #Snowflake #"ETL (Extract #Transform #Load)" #Data Lineage #Data Quality #Metadata #Python #Automation #Scala #Data Access #SQL (Structured Query Language) #Data Layers #Data Architecture #Data Processing #AI (Artificial Intelligence)
Role description
Senior Data AI Engineer (Snowflake / Semantic Modeling / Agentic AI)
We're looking for a Senior Data AI Engineer to help build the foundation for next-generation AI and analytics capabilities within a healthcare payer environment. This role will focus on designing Snowflake-based semantic data assets that power trusted analytics, natural language querying, and agentic AI-driven insights.
The ideal candidate brings deep Snowflake expertise, strong semantic modeling experience, and a passion for building scalable data products that enable both business users and AI-powered solutions to access and understand data more effectively.
What You'll Be Doing
• Design and implement scalable Snowflake data models and pipelines supporting analytics and Agentic AI initiatives
• Build and maintain bronze, silver, and gold data layers using medallion architecture principles
• Develop semantic views, business metrics, dimensions, and reusable data assets that support self-service analytics and natural language data access
• Partner with product, analytics, and engineering teams to translate business requirements into governed data products
• Optimize Snowflake performance, transformations, and data architecture for scalability and reliability
• Implement data quality validation, profiling, testing, and governance practices
• Support Snowflake Cortex-enabled analytics, semantic intelligence, and AI-assisted workflows
• Document semantic definitions, data lineage, and architectural standards
Required Experience
• Healthcare or payer industry experience (member, claims, provider, quality, or reference data)
• Expert-level Snowflake SQL skills, including complex transformations, CTEs, advanced joins, and analytic/window functions
• Strong experience building Snowflake data solutions using medallion architecture (bronze, silver, gold)
• Hands-on semantic modeling experience including metrics, dimensions, grain, relationships, and semantic views
• Experience validating data quality, profiling datasets, and ensuring trustworthy business outputs
• Strong communication skills and ability to work cross-functionally with product, analytics, and engineering teams
Preferred Experience
• Snowflake Cortex, semantic intelligence, or AI-enabled analytics solutions
• Agentic AI, natural language analytics, or AI-assisted engineering workflows
• dbt development and governed self-service analytics environments
• Python for automation, metadata processing, validation, or AI-related engineering initiatives
• Experience evaluating, troubleshooting, and optimizing AI agent performance
This is an exciting opportunity to help shape the future of AI-powered analytics by building trusted semantic data foundations that support both business users and intelligent agent-driven solutions.
Senior Data AI Engineer (Snowflake / Semantic Modeling / Agentic AI)
We're looking for a Senior Data AI Engineer to help build the foundation for next-generation AI and analytics capabilities within a healthcare payer environment. This role will focus on designing Snowflake-based semantic data assets that power trusted analytics, natural language querying, and agentic AI-driven insights.
The ideal candidate brings deep Snowflake expertise, strong semantic modeling experience, and a passion for building scalable data products that enable both business users and AI-powered solutions to access and understand data more effectively.
What You'll Be Doing
• Design and implement scalable Snowflake data models and pipelines supporting analytics and Agentic AI initiatives
• Build and maintain bronze, silver, and gold data layers using medallion architecture principles
• Develop semantic views, business metrics, dimensions, and reusable data assets that support self-service analytics and natural language data access
• Partner with product, analytics, and engineering teams to translate business requirements into governed data products
• Optimize Snowflake performance, transformations, and data architecture for scalability and reliability
• Implement data quality validation, profiling, testing, and governance practices
• Support Snowflake Cortex-enabled analytics, semantic intelligence, and AI-assisted workflows
• Document semantic definitions, data lineage, and architectural standards
Required Experience
• Healthcare or payer industry experience (member, claims, provider, quality, or reference data)
• Expert-level Snowflake SQL skills, including complex transformations, CTEs, advanced joins, and analytic/window functions
• Strong experience building Snowflake data solutions using medallion architecture (bronze, silver, gold)
• Hands-on semantic modeling experience including metrics, dimensions, grain, relationships, and semantic views
• Experience validating data quality, profiling datasets, and ensuring trustworthy business outputs
• Strong communication skills and ability to work cross-functionally with product, analytics, and engineering teams
Preferred Experience
• Snowflake Cortex, semantic intelligence, or AI-enabled analytics solutions
• Agentic AI, natural language analytics, or AI-assisted engineering workflows
• dbt development and governed self-service analytics environments
• Python for automation, metadata processing, validation, or AI-related engineering initiatives
• Experience evaluating, troubleshooting, and optimizing AI agent performance
This is an exciting opportunity to help shape the future of AI-powered analytics by building trusted semantic data foundations that support both business users and intelligent agent-driven solutions.






