Manager, Engineering (Data Platform)

Garner’s mission is to transform the healthcare economy, delivering high-quality and affordable care for all. We are fundamentally reimagining how healthcare works in the U.S. by partnering with employers to redesign healthcare benefits using clear incentives and powerful, data-driven insights. Our approach guides employees to higher-quality, lower-cost care, creating a system that works better for everyone. Patients achieve better health outcomes, employers spend healthcare dollars more effectively, and physicians are rewarded for delivering exceptional care rather than performing more procedures. Garner is one of the fastest-growing healthcare technology companies in the country. Our products are trusted by the most sophisticated employers and providers in the industry, and we are building a team of talented, mission-driven individuals who are motivated to make a meaningful impact on healthcare at scale. About the role: We are seeking an execution-focused and visionary Data Engineering Manager to lead our Data Platform Team. In this critical role, you will manage a team of talented engineers dedicated to building the common, reusable abstractions and high-throughput data infrastructure that power Garner’s internal and external applications. You will champion an AI-native development philosophy and scale our data pipeline capabilities, ensuring our systems seamlessly support the heavy computational demands of our next phase of company-wide growth. Where you will work: This role will be based in our New York City office (in the Financial District). You must be willing to work in the office 3 days per week on Tuesday, Wednesday and Thursday. What you will do: Lead and manage the Data Platform Engineering team, owning the end-to-end design, implementation, and operational excellence of systems that process complex healthcare data Provide high-quality technical contributions and architectural guidance, establishing robust standards for data modeling, processing, and system maintainability Build and optimize common data abstractions, pipelines, and frameworks designed for high scalability, ensuring our platform keeps pace with exponential enterprise data growth Translate complex, ambiguous business and data requirements into well-scoped, accurately estimated, and composable architectural pieces Foster and drive an AI-native engineering culture within the team, integrating cutting-edge AI tools and integrations to enhance development workflows and automate data operations Manage and grow stakeholder relationships across Engineering and Product, aligning team priorities with departmental OKRs and broader business goals Mentor, coach, and guide your team members, conducting detailed design reviews and managing robust Root Cause Analyses (RCA) to continuously elevate technical rigor The ideal candidate has: 5+ years of hands-on engineering experience, with a focus on Big Data and distributed system and infrastructure 2+ years of managing engineering teams, with a track record of building and mentoring high performing teams Expertise with batch data processing frameworks such as Hadoop, Spark, EMR, etc. Experience with stream processing systems such as Kafka and RedPanda Proficiency with technologies such as Temporal, Apache iceberg, AWS glue, Spark, DBT, and Soda Exhibits strong ownership and a proactive mindset, with a proven ability to translate complex business needs into scalable, actionable technical roadmaps Demonstrated ability to operate effectively in dynamic, fast-paced startup environments, with a hands-on approach and a strong commitment to organizational success Preference for managing healthcare data standards (e.g. HIPAA, EDI) A desire to be a part of our mission to improve the U.S. healthcare system A desire to be a part of a high-performing, mission-driven team that operates with intense urgency, a strong sense of individual accountability, and a commitment to authentic feedback Technologies we use: Python, Spark, dbt