Senior Data & AI Lakehouse Architect (Snowflake)

Title: Senior Data & AI Lakehouse Architect

Overview Healthcare organization is investing in data and analytics at the Enterprise level and looking to hire a fully hands-on data architect to own the data model for the enterprise Snowflake lakehouse, supporting both structured analytics and unstructured AI/ML use cases across the organization.

This role works closely with a dedicated data engineering team, architecting and proving out solutions hands-on, while engineering owns production build-out at scale. This is an individual contributor role. You won’t be managing a team or presenting roadmaps from a deck, you’ll be designing, modeling, and proving out the data architecture directly, onboarding new use cases as the business needs them.

What You’ll Do

• Own and evolve the data model for the enterprise Snowflake lakehouse, validating approaches hands-on with SQL and Python before handing designs to the data engineering team to build at production scale
• Apply strong data modeling judgment for structured analytics (star schema, Kimball, Data Vault), using modern, cloud-based, collaborative modeling and diagramming tools (i.e., SqlDBM, Lucidchart, Miro, Gliffy)
• Apply modeling approaches for semi-structured and unstructured AI/ML data: schema-on-read, Data Vault satellites, JSON/variant storage, medallion pipelines, and chunking/embedding for RAG, using GUI tools for design and code-based tools (dbt, Python) for building pipelines
• Compare and validate technical alternatives, including current cloud-native architecture patterns like federated query engines (Trino/Starburst), data virtualization, data mesh, and data fabric, and prove approaches out with hands-on POCs before they scale
• Determine the right data integration pattern for each use case, batch, streaming, CDC, or ELT, rather than defaulting to one approach
• Define data governance, security, and compliance standards across data assets, applied practically, not just conceptually
• Collaborate closely with the data engineering team, data scientists, and business stakeholders to translate requirements into working solutions

More Info:

• 1000% hands-on role
• full-time MOSTLY REMOTE role w/ minimal travel to HQ

Responsibilities/Experience:

• Hands-on, current experience in cloud data architecture, data modeling, and data integration, not just theoretical or dated knowledge
• Strong SQL and Python skills
• Real experience with Snowflake, ideally including migration work
• Strong data modeling background, both structured (star schema, Kimball, Data Vault) and unstructured/AI-ready approaches
• Healthcare industry experience, ideally within a health system

Ping Me: [email protected]