Healthcare Enterprise Data Warehousing Security & Analytics Engineering Architect

MDAEdge is seeking a Healthcare Enterprise Data Warehousing Security & Analytics Engineering Architect to lead the architecture, engineering, and optimization of a mission-critical data foundation. This role involves blending high-level data architecture and CI/CD rigor with healthcare compliance expertise to scale a secure data platform while mentoring a high-performing engineering team.

Responsibilities:

• Lead, mentor, and develop a high-performing team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement
• Architect and manage scalable data warehouse and lakehouse solutions on Databricks and Azure, ensuring maximum security and healthcare regulatory compliance
• Evaluate and implement AI/Machine Learning technologies within the environment to optimize data processes and accelerate advanced analytics
• Implement DevSecOps principles, integrating security, compliance, and automation into every stage of the development lifecycle
• Develop and manage CI/CD pipelines to enable automated testing, deployment, and environment consistency across all data workflows
• Oversee data modeling, integration, and quality frameworks to ensure accuracy, consistency, and organizational trust in analytic data sets
• Partner with Analytics, IT, and business stakeholders to deliver data solutions that align with clinical and operational needs

Requirements:

• Proven expertise in architecting and implementing Databricks solutions (not just usage), including Delta Lake, Apache Spark, and MLflow
• Hands-on experience building complex, production-grade data pipelines using Spark and Delta Lake
• Deep experience deploying analytics infrastructure on Microsoft Azure (e.g., Data Factory, Azure SQL, Azure Storage, Synapse)
• Demonstrated experience implementing DevSecOps frameworks and secure data operations within a regulated industry (Healthcare experience strongly preferred)
• Strong proficiency in CI/CD, Infrastructure-as-Code, and automation platforms like GitHub Actions or Azure DevOps
• Bachelor's or Master's degree in Computer Science, Information Systems, Data Engineering, or a related technical field
• Progressive experience in data engineering or data warehouse architecture
• Prior experience in a technical leadership role (e.g., Lead Engineer, Architect, or Engineering Manager) with hands-on architectural ownership
• Current of direct people management experience, including performance management and team development