Senior Data Engineer (Azure)

RAAPID is a leading healthcare technology innovator specializing in AI-enabled risk adjustment solutions. Funded by Microsoft and Great Place to Work-certified organization, we serve payers, healthcare providers, and support organizations with cutting-edge technology solutions that optimize revenue, ensure compliance, and reduce administrative costs. Why RAAPID?

• Backed by Microsoft: Proudly funded by M12, Microsoft's venture fund, validating our technology innovation and market potential
• Industry Pioneer: Leveraging state-of-the-art artificial intelligence, machine learning, vision AI, and knowledge graphs to transform healthcare operations
• Strong Foundation: Built on four key pillars - Trust, Technical Competence, Stability, and Technical Innovation
• Recognition: Proud recipient of HITRUST certification, demonstrating our commitment to security and compliance
• Culture: Certified Great Place to Work, reflecting our dedication to employee satisfaction and professional growth
• Mission-Driven: Focused on revolutionizing value-based healthcare through customizable, AI-powered solutions
• Global Presence: Headquartered in Louisville, Kentucky, with a robust team of over 100 employees across the US and India

Role Summary

We are hiring a Senior Data Engineer to drive the development of scalable, high-performance data pipelines for a migration project to a modern Azure Native architecture. This role will be instrumental in building an AI-ready data platform using Microsoft Fabric (Fabric IQ) and enabling seamless integration with AI/ML workflows (Foundry IQ).

• Design and build robust, scalable data pipelines (batch + near real-time) using Microsoft Fabric (Data Pipelines, Lakehouse)
• Lead migration of existing pipelines (AKS/custom ETL) to Fabric-native architecture
• Implement Medallion Architecture (Bronze → Silver → Gold) for structured and unstructured healthcare data
• Develop and optimize data models and transformations for analytics and AI use cases

Build ingestion frameworks for:

• APIs (FHIR, EHR systems)
• Files (JSON, HL7, CSV)

• Ensure data quality, validation (FHIR/claims), and observability across pipelines

Enable AI/ML workflows by preparing datasets for:

• RAG pipelines
• Feature engineering and model consumption

• Optimize pipeline performance, cost, and scalability
• Collaborate with Architects, AI/ML engineers, and Product teams to translate requirements into data solutions
• Mentor junior engineers and drive engineering best practices

Languages: Python, PySpark, SQL (advanced) Azure / Fabric:

• Microsoft Fabric (preferred) OR Azure Data Factory, Synapse, Data Lake

Data Architecture:

• Lakehouse, Medallion Architecture
• Batch + streaming data processing

Data Handling:

• JSON, Parquet, CSV, API integrations

Performance Optimization:

• Partitioning, indexing, query tuning