• Team Development: Lead, mentor, and manage a team of Data Engineers, fostering a culture of ownership, continuous improvement, and technical excellence. • Cross-Functional Partnering: Serve as the primary liaison between the Data Engineering team and other departments (Client Success, Partnerships, Product, Engineering, Clinical, and Business Intelligence) to translate business needs into technical requirements and roadmaps. • Project Management: Work with leadership, stakeholders, and product managers to coordinate roadmap commitments, keep projects on track, and communicate and roll with changes as they inevitably occur. • Process Improvement: Drive the adoption of DevOps and DataOps methodologies, automating workflows, improving deployment processes, and reducing manual operational burden. • Operational Excellence: Oversee daily data operations of our Data Platform, including monitoring, incident response, and performance tuning of data pipelines and databases to ensure high uptime and meet defined SLAs. • Data Quality & Governance: Implement proactive data quality checks and monitoring frameworks. Partner with stakeholders to establish and enforce data governance policies. • HIPAA & Compliance: Ensure all data operations and infrastructure adhere strictly to healthcare regulatory requirements, including HIPAA and other relevant data privacy standards. • Disaster Recovery: Develop and maintain robust backup, recovery, and business continuity plans for critical data assets. • Architect and Build: Lead the design and implementation of scalable, reliable, and performant ETL/ELT data pipelines and data warehouse solutions that meet the demands of a growing organization. • Multi-Cloud Infrastructure: Own and optimize the data infrastructure across AWS and Azure cloud environments, ensuring interoperability, cost efficiency, and robust security. • Technology Expertise: Drive the selection and adoption of best-in-class data technologies, including modern data warehouses (e.g., Snowflake, Azure Synapse), orchestration tools (e.g., AWS Glue, Azure Data Factory), and real-time streaming solutions. • Code Quality: Set and enforce standards for code quality, testing, version control (Git), and documentation for all data engineering projects.