Director, Data & Analytics Engineering

Responsibilities

• Own the warehouse and pipeline architecture that powers the Charlie Health World Model, the causal, continuously updated representation of our ecosystem that fuels reporting, product analytics, and the agentic Intelligence Layer
• Drive the long-term roadmap for AI-ready data: real-time signal graphs beyond batch cycles, schema-validated event flows, and semantic retrieval surfaces for transcripts, notes, and other long-form artifacts
• Define and execute a vision for scalable data model architecture in Snowflake, evolving 1,600+ existing dbt models toward extensible, well-governed, agent-consumable patterns
• Partner with Machine Learning, Data Science, Engineering, Product, and BizOps to align data initiatives with company priorities and unlock new opportunities, particularly the agentic capabilities riding on top of the World Model
• Lead execution end-to-end: sprint ceremonies, roadmap planning, and prioritization, with the discipline to keep a growing team shipping high-quality, reliable solutions on schedule
• Oversee data integrity, documentation, testing, monitoring, and provenance across systems so that stakeholders, human and agent, can trust and self-serve on our data
• Guide and contribute to architecture and design decisions across our stack (Dagster, Snowflake, dbt, Fivetran, Hightouch, Hex, Tableau), and resolve critical technical issues as a hands-on technical leader
• Drive reliability, scalability, observability, security, and cost-efficiency improvements across the data stack, including the PHI gatekeeping and HITRUST-aligned patterns that govern signal ingestion
• Identify bottlenecks and implement improvements to team workflows, tools, and development practices
• Manage and mentor a growing team of Data and Analytics Engineers and one Data Engineering Manager. Operate as a Player-Coach: focus on craft, mentorship, high-leverage code review, and supporting DRIs running 90-day cross-cutting missions
• Define and maintain data governance standards and proactively manage stakeholder expectations to drive scalable, trusted data use

Requirements

• 10+ years of data or analytics engineering experience, with 4+ years managing and mentoring data and analytics engineers, with a focus on execution and delivery
• Proven ability to drive team operations, including sprint ceremonies, roadmap planning, and prioritization across multiple workstreams
• Hands-on background building and maintaining ELT pipelines using SQL, dbt, and OLAP databases like Snowflake
• Proficiency in Python (preferred) or another language strong enough to guide and review technical work
• Skilled at building scalable reporting solutions in Tableau or Hex and enabling self-serve analytics across the organization
• Strong data modeling, provenance, and governance skills to support extensible, trusted, and consistent reporting and patterns
• Track record of improving team processes, optimizing workflows, and delivering measurable impact
• Clear, concise communicator who can translate complex technical concepts for non-technical stakeholders
• Comfortable navigating ambiguity, breaking down complex problems, and driving iterative solutions
• Committed people leader with a history of coaching talent and fostering a high-performance, inclusive team culture