Senior Manager, Analytics Engineering

7+ years of experience in analytics engineering, data engineering, or a related field, with at least 2 years of people management experience.

Deep expertise in SQL, dbt, and Snowflake; strong understanding of dimensional modeling and data warehouse design patterns.

Experience building and leading high-performing data teams, including hiring, mentoring, and setting technical direction.

Hands-on proficiency with modern data stack tooling (dbt, Snowflake, Sigma or similar BI tools, Git, Python).

Demonstrated ability to bridge technical and business stakeholders — translating business requirements into data architecture decisions and communicating trade-offs clearly.

Track record of owning and delivering large-scale data initiatives with measurable business outcomes.

Excellent communication and stakeholder management skills, particularly in interfacing with senior leadership.

NICE TO HAVE

Experience implementing or managing a semantic layer (e.g., Snowflake Semantic Views, dbt Semantic Layer, etc.).

Familiarity with AI/ML data readiness, including building data foundations that support analytics automation and LLM-powered tooling.

Experience in subscription/DTC commerce, health/wellness, or consumer hardware.

Background in data governance, data contracts, or metrics layer standardization.