Senior Data Platform & Healthcare AI Analytics Engineer

MindCare Solutions is a premier provider of behavioral health services, supporting various clinical settings. They are seeking a Senior Data Platform & Healthcare AI Analytics Engineer to architect and build a healthcare data and analytics ecosystem, transforming fragmented healthcare data into actionable insights for improved patient outcomes and operational efficiency.

Responsibilities:

• Architect and operate the organization’s Azure / Microsoft Fabric healthcare data platform
• Design scalable ETL/ELT pipelines integrating EMR/EHR systems via HL7, FHIR APIs, and direct integrations
• Design and develop secure, scalable EMR interface APIs enabling bi-directional interoperability between Microsoft Dynamics 365 Health Cloud and partner EMRs, supporting clinical workflows (orders, documentation, patient context, care coordination) using HL7, FHIR, and modern API-based integration patterns
• Build, extend and maintain the lakehouse and warehouse environments using Microsoft Fabric, Azure Synapse, and Azure Data Lake
• Integrate healthcare data from EMRs, revenue cycle systems, telehealth platforms, scheduling systems, and external healthcare datasets
• Ensure reliability, scalability, and performance of the enterprise data platform
• Design and manage the Power BI analytics platform, including governance, workspaces, and enterprise datasets
• Build Power BI semantic models, reusable datasets, and reporting frameworks
• Deliver executive and operational dashboards supporting clinical, operational, and financial leaders
• Enable self-service analytics across the organization
• Analyze healthcare data to generate insights across core operational domains, including: provider productivity and utilization, patient access and scheduling performance, encounter lifecycle and clinical workflow efficiency, revenue cycle and claims performance, payer reimbursement and financial trends
• Translate complex healthcare datasets into clear insights that improve patient outcomes, operational performance, and financial sustainability
• Design and implement the data foundation for AI-driven healthcare analytics, including: predictive models for patient no-shows, provider capacity, and care demand, analytics to detect claims denials and revenue leakage, AI-assisted analytics using Azure Machine Learning, Fabric AI capabilities, and Azure OpenAI, enabling predictive and AI-driven insights within Power BI and analytics platforms
• Implement and maintain HIPAA-compliant data architecture protecting Protected Health Information (PHI)
• Deploy security practices including row-level security (RLS), data masking, encryption, and role-based access controls
• Establish data quality monitoring and validation frameworks to ensure reliable clinical and operational reporting
• Maintain detailed data lineage, documentation, and audit trails to support regulatory reporting (MIPS, MACRA, CMS quality programs)

Requirements:

• 7+ years' experience in Data Engineering, Analytics Engineering, or Data Platform roles
• 3+ years' experience working with healthcare data, including EMR/EHR and/or revenue cycle datasets
• Advanced expertise with the Microsoft Azure data platform, including: Azure Synapse, Azure SQL, Azure Data Factory, Microsoft Fabric
• Proven experience building enterprise Power BI platforms, including semantic models, datasets, governance, and dashboards
• Advanced proficiency in SQL (T-SQL) and experience with Python or Spark for data engineering, transformation, and analytics
• Strong experience designing scalable data pipelines and data models supporting AI, machine learning, and advanced analytics workloads
• Experience enabling AI-driven analytics, including preparation of datasets for predictive modeling and integration of AI insights into reporting platforms
• Experience designing or supporting API-driven and event-based architectures, including REST APIs and modern integration patterns
• Experience working with healthcare interoperability standards, including: HL7, FHIR APIs
• Ability to design systems supporting clinical workflows and data exchange across EMR systems
• Strong analytical mindset with ability to generate operational and financial insights from healthcare data
• Deep understanding of HIPAA, HITECH, and PHI data protection requirements
• Experience with behavioral health, telehealth, or outpatient healthcare organizations
• Experience designing and implementing bi-directional EMR integrations, including API-based interoperability between platforms such as Microsoft Dynamics 365 Health Cloud and partner EMRs
• Experience with healthcare data models, including OMOP or similar frameworks
• Experience building predictive analytics or AI-driven healthcare models (e.g., access, utilization, RCM optimization)
• Experience with agentic AI systems, including: AI orchestration frameworks, LLM integration (Azure OpenAI, ChatGPT, Claude), Retrieval-Augmented Generation (RAG), AI-driven workflow automation
• Experience integrating AI capabilities into analytics platforms (e.g., AI-assisted dashboards, automated insights)
• Experience supporting Revenue Cycle Management (RCM) analytics, including: claims lifecycle, denial management, reimbursement optimization
• Experience analyzing payer mix, reimbursement trends, and claims data
• Experience with Azure Machine Learning or similar ML platforms
• Microsoft certifications such as: Azure Data Engineer Associate, Power BI Data Analyst Associate