Senior Data Engineer (Founding Data Engineer)

Architect, build, and maintain a scalable cloud-based data warehouse or lakehouse environment. Design and implement robust ETL/ELT pipelines integrating data from clinical systems, internal tools, third-party APIs, and operational platforms. Develop clean, well-structured data models optimized for analytics, reporting, and data science. Implement data quality processes, validation layers, testing frameworks, and governance standards. Create and maintain metadata documentation, data dictionaries, lineage tracking, and schema definitions. Optimize warehouse performance, cost efficiency, and pipeline reliability. Evaluate tooling for orchestration, workflow automation, and observability.

Own end-to-end data ingestion processes ensuring stable, timely, and accurate data availability. Establish monitoring, alerting, logging, and operational observability for all pipelines. Troubleshoot and resolve data inconsistencies, ingestion failures, and system bottlenecks. Ensure PHI and HIPAA-compliant data access, storage, and transmission practices.

Collaborate with analytics and product teams to build source-of-truth datasets and KPI reporting layers. Partner with engineering to instrument data collection and event tracking across the platform. Enable self-service analytics by delivering clean, well-modeled data assets and clear documentation.

Build pipelines and data structures that support machine learning training, testing, and deployment. Prepare datasets for AI-driven features, RAG workflows, and real-time personalization. Support experimentation frameworks, A/B testing, and future intelligent system capabilities.

Work closely with product, engineering, operations, and clinical teams to understand data needs and deliver scalable solutions. Uphold HIPAA and best practices for secure PHI handling across all data environments.