Engineering Manager, Data

Millions of people across the country are navigating mental health conditions, substance use disorders, and eating disorders, but too often, they’re met with barriers to care. From limited local options and long wait times to treatment that lacks personalization, behavioral healthcare can leave people feeling unseen and unsupported.

Charlie Health exists to change that. Our mission is to connect the world to life‑saving behavioral health treatment. We deliver personalized, virtual care rooted in connection—between clients and clinicians, care teams, loved ones, and the communities that support them. By focusing on people with complex needs, we’re expanding access to meaningful care and driving better outcomes from the comfort of home.

As a rapidly growing organization, we’re reaching more communities every day and building a team that’s redefining what behavioral health treatment can look like. If you’re ready to use your skills to drive lasting change and help more people access the care they deserve, we’d love to meet you.

As the Engineering Manager, Data you will lead and represent a team of Data and Analytics Engineers, driving execution at a high level while fostering a culture of trust, empathy, and technical excellence. You will own the data warehouse and pipelines that power company‑wide reporting, product analytics, and all post‑source data operations, ensuring these are reliable, observable, accurate, fresh, scalable, and extensible.

You will provide structured execution, clear prioritization, and alignment with business needs. As a hands‑on leader, you will lead sprint ceremonies, roadmap planning, provide mentorship, remove blockers, contribute technically as needed, and create a culture of execution and continuous improvement. You will partner with leaders in our ML, Analytics, Biz Ops, and Engineering teams and define a vision for data model best practices in our warehouse and ETL pipeline architecture, while supporting new business initiatives.

• Drive the development of data pipelines and analytical products in the warehouse, ensuring reliable, performant systems and timely delivery of business‑critical insights.
• Work closely with business partners across Data Science, Machine Learning, Engineering, Product, and Biz Ops to align data initiatives with company needs and unlock new opportunities.
• Define a vision for a scalable data model architecture in the warehouse, and create a roadmap for the team to iterate into that end‑state.
• Lead execution, ensuring the team delivers high‑quality, reliable data solutions aligned with business priorities, including leading sprint ceremonies and road mapping.
• Oversee data integrity, documentation, testing, and monitoring across systems to ensure stakeholders can trust and self‑serve on our data.
• Guide and contribute to architecture and design decisions, resolve critical technical issues, and ensure scalable development across our data stack (Dagster, Snowflake, dbt, Fivetran, Hightouch, Hex, Tableau).
• Identify bottlenecks and implement improvements to team workflows, tools, and development practices.
• Manage and mentor a growing team of data engineers; foster a culture of technical excellence, accountability, and continuous improvement.
• Establish metrics to track progress, communicate priorities, and demonstrate business impact.
• Define and maintain data governance standards and proactively manage stakeholder expectations to drive scalable, trusted data use.
• Drive reliability, scalability, observability, security, and cost‑efficiency improvements across our data stack.
• Own company‑wide KPI reporting, including ad hoc analysis, product analytics, and dashboard development, ensuring the team delivers clear, accurate insights in response to evolving business questions.

• 2+ years managing and mentoring data and analytics engineers, with a focus on execution and delivery, and 6+ years of data or analytics engineering experience total
• Proven ability to drive team operations, including sprint ceremonies, roadmap planning, and prioritization
• Hands‑on background in building and maintaining ELT pipelines using SQL, DBT, and OLAP…