Principal Data Engineer

Core Competencies: Python, Advanced SQL, Apache Spark (or other big data technologies), & Apache Kafka (or other streaming technologies). 8+ years of engineering experience with a minimum of 3+ years demonstrated technical leadership. Proven record of building production-grade data infrastructure and platforms from inception. Experience with at least one Enterprise Data Platform (Snowflake, Databricks) in highly regulated environments. Multi-tenant system architecture experience with complex access and security requirements. Understanding of Lambda vs Kappa Architecture patterns. Hands-on experience with major cloud platforms (AWS, Azure, GCP) and their data services. Expertise in cloud-native data architectures and optimization. Containerization (Docker, Kubernetes) in production environments. Prior experience with IAC tools (Terraform preferred). Experience with role based access control, audit logging, and data governance. Knowledge of data security, encryption at rest/in transit, and tokenization. Prior experience working with PHI/PII and working in audited environments. HIPAA, SOC2, and HITRUST compliance requirements and implementation. Healthcare interoperability standards (FHIR, HL7) experience. EHR operational data and claims data processing experience.

Drive vendor evaluation and adoption of critical data platform tools. Architect and lead the implementation of a production-grade, multi-tenant data lake handling PHI at scale. Lead cross-functional implementation of new data infrastructure. Establish and maintain SLAs for critical data processing and availability. Create operational accountability frameworks for entire data pipeline lifecycle. Maintain legacy pipelines and processing while helping provide pathways to replace older systems with new tooling. Guide architectural decisions such that they balance immediate needs with long-term goals of scalability, compliances, and enhanced capabilities. Provide mentorship to existing team members.