Senior Data Engineer

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, data warehouses, transformations, 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 Senior Data Engineer on this team, you'll be a core technical contributor. 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 pipelines using Fivetran and DBT, with a strong emphasis on correctness, observability, and performance.
• Orchestrate complex data workflows using Dagster and DBT, ensuring reliable and well-monitored execution.
• 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 Tableau, collaborating with stakeholders to ensure data is accessible 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.
• 5+ years of experience in Engineering, with at least 3 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

• Experience with our specific tools (Fivetran, Dagster, Snowflake, DBT, Hex, and Hightouch) is a strong plus.
• Experience working with A