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
Required Experience
- 4 to 6 years of experience (3+ years in data engineering)
- Strong hands-on experience with Azure Data Platform
- Proven experience in building and optimizing large-scale data pipelines
- Experience in data platform modernization or migration projects
Nice to Have
- Experience with healthcare data (FHIR, claims, EHR)
- Exposure to RAG pipelines / vector databases / AI data prep ● Familiarity with event-driven architectures
- Understanding of data security & governance in regulated environments
Success Metrics
- High-quality, scalable pipelines delivered on time
- Seamless migration with minimal business disruption
- Improved data performance, reliability, and cost efficiency ● Strong enablement of AI/ML and analytics use cases
What We’re Looking For
- Strong hands-on engineer with ownership mindset
- Ability to operate in fast-paced, evolving architecture environment ● Problem-solver with focus on performance, scalability, and data quality ● Mentor and team player
Why This Role Matters
This role is critical to building the foundation of AI-first platform, enabling:
- Scalable data processing via Fabric IQ
- AI-driven intelligence via Foundry IQ
- Future-ready healthcare data platform