Engineering Manager, Analytics Engineering - Zus Health

Job Title: Engineering Manager, Analytics Engineering
Job Location: Boston, MA
Job Listing URL: https://jobs.lever.co/zushealth/6c789511-7058-4a38-a12f-f528d6b194b7
Job Description: Who we are

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 particular 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.

We’re hiring an Engineering Manager to lead this function as a player-coach. This person will build the team while remaining hands-on in designing and building analytical data products.

This role will shape how data engineering enables BI, AI, and agentic systems at Zus by producing high-quality, explainable datasets that accelerate AI-supported healthcare applications.

As part of our team, you will
Lead data engineering for 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.
You’ll Succeed If You Have

Expert SQL and data modeling

Expert ETL skills using dbt or similar frameworks

Experience managing or mentoring analytics and data engineers.

Experience Modern cloud data warehouses and lakes (e.g. Snowflake, BigQuery, SparkSQL)

Experience with automation and data reliability practices (testing, monitoring, CI/CD)

Facility with modern BI tools and semantic modeling (Sigma preferred)

Strong hands-on experience building production analytical data products.

Ability to balance people leadership with hands-on technical work.

It’s a Plus If You

Are experienced working with healthcare data such as FHIR, clinical datasets, or claims.

Have knowledge of Value-Based Healthcare concepts and systems.

Have experience building datasets for machine learning or AI systems

Are interested in building data systems that enable AI-driven healthcare applications.

Enjoy building and leading teams while still remaining hands-on.

Have built analytics systems that power products, workflows, or AI systems—not just dashboards.

Are excited about using LLMs and agentic AI to improve healthcare workflows and analytics systems.

Like designing clean semantic layers and trusted data models that teams can build on.

Enjoy working in early-stage environments where you can shape architecture, standards, and team culture.

Are in the Boston metro and excited to collaborate in person on a hybrid schedule, or are remote (EST/CST) but willing to travel for in person collaboration occasionally