Staff Data Engineer

Staff Data Engineer

New York, NY

Why Charlie Health?

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.

About the Role

The Analytics & Data Engineering team owns all post-transactional data operations that turn raw data into insights. We design and operate ETL pipelines, Kafka Topics, data warehouses, transformations, agentic skills, and analytics tooling that power reporting, experimentation, and decision-making across Charlie Health. Our focus is on reliability, scalability, and making data accessible and actionable for the entire organization.

As a Staff Data Engineer on this team, you'll be a key technical contributor and mentor across the team. You will build and own significant parts of our data infrastructure, driving pipeline reliability and warehouse quality. You'll work across a modern data stack to ensure that Charlie Health's data is timely, accurate, performant, secure, and trusted. If you're energized by the opportunity to expand access to mental healthcare and make a meaningful impact on millions of lives from the data and pipelines you support, we'd love to hear from you.

Responsibilities

• Build, release, and maintain high-quality ELT & streaming pipelines with a strong emphasis on correctness, observability, and performance.
• Orchestrate complex data workflows using Dagster/Airflow and DBT, ensuring reliable and well-monitored execution and quality assessments.
• Own meaningful areas of our data warehouse, Snowflake, designing well-modeled, performant schemas, and maintaining clear documentation of data definitions and lineage.
• Resolve critical data issues independently and proactively identify and address bottlenecks before they impact downstream consumers.
• Contribute to architectural decisions and technical design discussions, bringing well-reasoned, data-driven recommendations to the team.
• Support analytics delivery through Hex and AI Agents, collaborating with stakeholders to ensure data is accessible, governed, and actionable.
• Help the team level up by authoring documentation, sharing learnings, and contributing to a culture of craft and continuous improvement.
• Participate in our on-call rotation to ensure data availability and pipeline health.

Requirements

• Bachelor's degree in Computer Science, Mathematics, or a related technical discipline, or equivalent practical experience.
• 7+ years of experience in Data, with at least 4 years in a Data Engineering role.
• Deep expertise in analytical use cases of SQL, including CTEs, window functions, aggregation patterns, and performance tuning techniques such as partitioning and clustering.
• Strong proficiency in Python, including experience with common data engineering libraries.
• Hands-on experience with a modern data stack
• Demonstrated ability to take ownership of loosely-defined problems, breaking them into well-scoped tasks, driving them to completion, and communicating tradeoffs clearly.
• Experience working with sensitive data in a regulated environment.
• You live within a 75-minute commute of our NYC office (near Union Square) and are able to work in-office 4 days per week.

Nice to Haves

• Previous Experience in Healthcare
• Previous Experience in Airflow & Migrations.
• Previous Experience with Kafka Streams
• Experience leveraging AI tools for development

Our Values

• Connection: Care deeply & inspire hope.
• Congruence: Stay curious & heed the evidence.
• Commitment: Act with urgency & don't give up.