Data Engineer, AI/ML Specialist

Requirements

• Data Engineering: Design, implement, and optimize OCR and data extraction pipelines for ingesting PDF referral forms and other healthcare documents.
• Develop data transformation and mapping processes to store extracted data into an Azure SQL schema.
• Build and maintain the medallion data architecture (Bronze/Silver/Gold) in Azure Data Lake Storage to support both application workflows and future analytics/model training.
• Implement and optimize search indexing (Azure AI Search) for both structured and unstructured data.
• AI/ML Development: Integrate Azure OpenAI or equivalent LLM services with retrieval-augmented generation (RAG) to support a natural language query feature.
• Implement initial predictive analytics models (fall risk, infection risk, medication cost forecasting) using heuristics or light ML models, with a path to more advanced modeling in Phase 2.
• Develop a compliance AI agent (MVP version) that runs scheduled checks on documentation and flags potential violations.
• Collaborate with the Solution Architect to ensure AI components are secure, HIPAA-compliant, and cost-optimized.
• Collaboration & Delivery: Work in Azure DevOps with sprint-based development, pairing with backend/API developers on AI integration points.
• Participate in architecture/design reviews and provide input on data model decisions.
• Document pipelines, AI integrations, and data flows for future handoff to the client’s internal team.
• Support UAT for AI/data features, including tuning models and validating extracted data.
• Required Skills & Experience: Technical Expertise
• Proven experience with Azure Data Services (Azure SQL, Data Lake Storage, Azure AI Search, Azure Functions).
• Hands-on experience with OCR (Azure Form Recognizer / Azure Document Intelligence) and unstructured data processing.
• Strong Python skills for AI pipeline and data processing development.
• Experience integrating LLMs (Azure OpenAI) with RAG patterns.
• Knowledge of basic predictive modeling techniques (classification, regression) and healthcare data compliance considerations.
• Proficiency with REST APIs for integrating external systems (e.g., pharmacy, insurance).
• Healthcare & Compliance
• Understanding of HIPAA compliance and secure handling of PHI.
• Familiarity with healthcare data formats and workflows (HL7, FHIR, eMAR).
• Collaboration & Delivery
• Prior experience working in agile, cross-functional product teams.
• Ability to deliver end-to-end—from data ingestion to model integration to API exposure.
• Strong documentation and knowledge transfer skills.
• Preferred Qualifications
• Experience in healthcare software development (EHR, EMR, or related domains).
• Familiarity with vector search and semantic search concepts.
• Experience with Azure Machine Learning for model deployment.
• Background in predictive analytics for healthcare outcomes.