Healthcare Enterprise Data Warehousing Security & Analytics Engineering Architect

Healthcare Enterprise Data Warehousing Security & Analytics Engineering ArchitectOur client is seeking a Healthcare Enterprise Data Warehousing Security & Analytics Engineering Architect to lead the architecture, engineering, and optimization of a mission-critical data foundation. Built on Databricks and Azure, this platform enables scalable analytics that directly power care delivery for vulnerable seniors.This is a unique opportunity for a true hands-on technical leader not just a people manager. As the Subject Matter Expert (SME) in Databricks, Azure Data Services, and DevSecOps, you will build a compliant, AI-enabled lakehouse from the ground up. You will blend high-level data architecture and CI/CD rigor with healthcare compliance expertise to scale a modern, secure data platform while mentoring a high-performing, innovation-driven engineering team.Key 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.Must-Have Technical Skills: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.Professional Experience: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.