Engineering Manager, Analytics Engineering
About The Position
Zus is a shared health data platform designed to accelerate healthcare data interoperability by providing easy-to-use patient data via API, embedded components, and direct EHR integrations. Founded in 2021 by Jonathan Bush, co-founder and former CEO of athenahealth, Zus partners with HIEs and other data networks to aggregate patient clinical history and then translates that history into user-friendly information at the point of care. Zus's mission is to catalyze healthcare's greatest inventors by maximizing the value of patient insights - so that they can build up, not around. Zus is building a clinical data-first analytics foundation for providers with a focus on value-based care (VBC). Our data powers longitudinal care management across areas like medication adherence, care gap closure, risk stratification, and transitions of care. Weâre hiring an Engineering Manager, to lead this function as a player-coach. This person will grow the team while remaining hands-on in designing and building analytical data products. This role will shape how analytics engineering enables BI, AI, and agentic systems at Zus by producing high-quality, explainable datasets that accelerate AI-supported healthcare applications.
Requirements
- Expert SQL and analytical data modeling
- Experience with dbt or similar analytics engineering frameworks
- Experience with modern cloud data warehouses and lakes (Snowflake, BigQuery, SparkSQL)
- Deep automation and data reliability practices (testing, monitoring, CI/CD)
- Understanding of modern BI tools and semantic modeling (Sigma preferred)
- Experience building datasets for machine learning or AI systems
- Experience with data transformation and workflow orchestration tools such as dbt and airflow
- Strong hands-on experience building production analytics systems.
- Experience working with healthcare data such as FHIR, clinical datasets, or claims.
- Experience managing or mentoring analytics/data engineers.
- Ability to balance people leadership with hands-on technical work.
- Interest in building data systems that enable AI-driven healthcare applications.
Responsibilities
- Build analytics systems
- Design and build production-grade analytical data models and datasets.
- Translate healthcare data (FHIR, claims, etc.) into reusable analytics assets.
- Develop semantic layers and datasets that power workflows, analytics, and AI/ML applications.
- Perform data engineering tasks (data transformation and workflow orchestration) to reliably land these tables.
- Enable AI-driven data systems
- Create structured datasets that support model training, feature engineering, and feedback loops.
- Partner with AI and Data Science teams to accelerate LLM and agentic AI capabilities.
- Own analytics architecture
- Define the analytics-layer architecture from foundational models to workflow-ready datasets.
- Partner with Platform Engineering on ingestion, storage, performance, and scalability.
- Implement data quality, governance, and observability.
- Lead the team
- Hire, manage and mentor analytics engineers.
- Establish standards for modeling, testing, and documentation.
- Lead through coaching, code reviews, and hands-on technical leadership.
Benefits
- Competitive compensation that reflects the value you bring to the team a combination of cash and equity
- Robust benefits that include health insurance, wellness benefits, 401k with a match, unlimited PTO
- Opportunity to work alongside a passionate team that is determined to help change the world (and have fun doing it)
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Manager
Education Level
No Education Listed
Number of Employees
11-50 employees
