AIData Engineer

AI/Data Engineer


We are seeking an AI Data Integration Engineer with strong hands-on experience in Snowflake healthcare claims
data and practical AI/LLM integration.
This role will lead the creation of a sanitized claims data layer (Snowflake views models and pipelines) used by
internal and external AI systems to identify insights patterns savings opportunities and potential issues for our
members and clients.
Preferred candidates will also have experience integrating AI solutions in Azure AI Foundry enabling us to scale
toward enterprise-level AI agents copilots and analytics capabilities in the future.
This role sits at the intersection of data engineering AI development and healthcare domain expertise.

MINIMUM REQUIREMENTS (REQUIRED TO HIRE)
Technical
3 years of hands-on Snowflake experience including:
o SQL semi-structured data (JSON) UDFs
o Secure Views & Masking Policies
o Data modeling (Star/Snowflake schemas)
o Performance optimization
Strong experience building ETL/ELT pipelines in a modern data stack.
At least 1-2 years of applied AI/LLM development including:
o Designing prompt pipelines
o Calling LLM APIs (Azure OpenAI OpenAI Anthropic etc.)
o Integrating structured data into LLM workflows
Previous work with healthcare or claims datasets (medical or pharmacy).
Strong understanding of HIPAA privacy principles de-identification strategy and PHI minimization.
Soft Skills
Clear written and verbal communication.
Ability to translate product requirements into technical solutions.
Comfortable working in a fast-paced evolving environment.
Highly collaborative; strong problem-solving mindset.

PREFERRED QUALIFICATIONS (STRONG PLUS)
Azure & Enterprise AI
Experience with Azure AI Foundry including:
o Model catalog & deployments
o Agents / tool-calling workflows
o Responses API
o Vector indexing and retrieval
Experience with Azure OpenAI in a HIPAA environment.
Familiarity with Health Data Services FHIR or Fabric Healthcare Data Solutions.
Advanced Data & AI
Experience building RAG pipelines vector embeddings semantic search.
Experience designing AI-driven analytics copilot-style solutions or automated insights tools.
Background in ML Ops data governance or data privacy engineering.
Healthcare Domain
PBM or payer experience (pharmacy claims accumulators benefit design).
Experience generating insights such as:
o Cost driver analysis
o Adherence metrics
o Trend & utilization insights
o Plan optimization / savings recommendations
Previous work supporting clinical actuarial or analytics teams.

SUCCESS CRITERIA (HOW PERFORMANCE WILL BE EVALUATED)

o Snowflake sanitized views delivered validated and securely deployed.
o AI integration produces accurate explainable insights consistently.
o Reduction in manual analysis time for internal teams.
o High-quality documentation and reproducible pipelines.
o Successful prototype or pilot for Azure AI Foundry-based expansion.
o Trusted partnership with product clinical and engineering teams.

TOOLS & TECHNOLOGIES USED
Required:
Snowflake SQL ETL/ELT tools (DBT Matillion Airflow etc.) Python APIs LLMs (Azure OpenAI or OpenAI) Git.

Preferred:
Azure AI Foundry Azure Functions Azure Service Bus Fabric FHIR APIs Databricks (optional) Vector DBs.

Required Skills:

PYTHONAZURE SERVICEAZUREAPISGITSQLAI