AI Data Integration Engineer (Snowflake + Healthcare Analytics)

job summary: ROLE AND RESPONSIBILITIES

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.

location: Telecommute job type: Contract to Perm salary: $65 - 85 per hour work hours: 8am to 4pm education: Bachelors

responsibilities: CORE RESPONSIBILITIES

Snowflake Data Engineering (Primary Responsibility)

• Design, develop, and maintain sanitized, de-identified views in Snowflake for AI consumption.

• Implement robust ETL/ELT transformations to prepare claims, pharmacy, member, and utilization data for

downstream AI and analytics workflows.

• Build reusable data models, UDFs, and stored procedures to compute derived metrics (e.g., utilization

flags, cost drivers, adherence metrics, risk markers).

• Ensure data structures follow HIPAA privacy, minimization, and de-identification best practices.

• Collaborate with product and AI teams to define minimal-but-sufficient data schemas for AI analysis.

AI Integration & Feature Development

• Build the first version of a claims insight engine using LLMs (Azure OpenAI, OpenAI, or similar) grounded

on Snowflake data.

• Create schemas and payloads to feed structured data into AI prompts or agent pipelines.

• Produce structured outputs such as:

• Patterns in claims behavior

• Cost savings opportunities

• Potential issues in plan design

• Member-level or population-level recommendations

• Explanation narratives suitable for clients or internal teams

• Work with the product team to design LLM prompt strategies, guardrails, and output formatting.

Data Governance & Compliance

• Implement data privacy controls, PHI minimization, and secure access layers within Snowflake.

• Work with compliance teams to validate that AI inputs follow regulatory and organizational standards.

• Maintain auditability and logging for data access and AI interactions.

Collaboration

• Partner with product managers, analysts, and AI engineers to understand requirements and translate

them into technical deliverables.

• Educate internal teams on how the AI insights layer works (Snowflake view, AI input, AI output patterns).

• Participate in roadmap planning to evolve the claims AI platform into a scalable enterprise solution.

qualifications: 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.

Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.

At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.

Pay offered to a successful candidate will be based on several factors including the candidate’s education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility).

This posting is open for thirty (30) days.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

,

CORE RESPONSIBILITIES

Snowflake Data Engineering (Primary Responsibility)

• Design, develop, and maintain sanitized, de-identified views in Snowflake for AI consumption.

• Implement robust ETL/ELT transformations to prepare claims, pharmacy, member, and utilization data for

downstream AI and analytics workflows.

• Build reusable data models, UDFs, and stored procedures to compute derived metrics (e.g., utilization

flags, cost drivers, adherence metrics, risk markers).

• Ensure data structures follow HIPAA privacy, minimization, and de-identification best practices.

• Collaborate with product and AI teams to define minimal-but-sufficient data schemas for AI analysis.

AI Integration & Feature Development

• Build the first version of a claims insight engine using LLMs (Azure OpenAI, OpenAI, or similar) grounded

on Snowflake data.

• Create schemas and payloads to feed structured data into AI prompts or agent pipelines.

• Produce structured outputs such as:

• Patterns in claims behavior

• Cost savings opportunities

• Potential issues in plan design

• Member-level or population-level recommendations

• Explanation narratives suitable for clients or internal teams

• Work with the product team to design LLM prompt strategies, guardrails, and output formatting.

Data Governance & Compliance

• Implement data privacy controls, PHI minimization, and secure access layers within Snowflake.

• Work with compliance teams to validate that AI inputs follow regulatory and organizational standards.

• Maintain auditability and logging for data access and AI interactions.

Collaboration

• Partner with product managers, analysts, and AI engineers to understand requirements and translate

them into technical deliverables.

• Educate internal teams on how the AI insights layer works (Snowflake view, AI input, AI output patterns).

• Participate in roadmap planning to evolve the claims AI platform into a scalable enterprise solution.

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.