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Charlie Health · 1 day ago

Engineering Manager, Data

New York, NY

Full-time

Onsite

Senior Level

$200K/yr - $265K/yr

6+ years exp

Charlie Health is a rapidly growing organization focused on providing life-saving behavioral health treatment through personalized virtual care. As the Engineering Manager, Data, you will lead a team of Data and Analytics Engineers, driving execution and ensuring the reliability and performance of data pipelines and analytics products.

Health Care

Responsibilities

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 BizOps 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 roadmapping

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

Qualification

Data engineering managementELT pipeline developmentData modelingSQL proficiencyPython programmingTableau reportingWorkflow orchestrationTeam mentorshipProcess improvementHealthcare data standardsAWS technologiesCross-functional collaborationEffective communication

Required

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 databases like Snowflake

Proficiency in one or more programming languages (Python preferred), with the ability to guide and review technical work

Experience with workflow orchestration tools like Dagster, Airflow, Prefect

Skilled in developing scalable reporting solutions using tools like 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

Experience being an effective cross-functional partner with Machine Learning, Product, Analytics, and Engineering, aligning data work with business goals

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

Please note: candidates located within a 75-minute commute of our NYC office are expected to work onsite 4 days/week