Design and implement robust data architecture capable of handling hundreds of terabytes and a 10x growth trajectory while maintaining performance and reliability.
Lead data quality initiatives across the organization, implementing observability and monitoring solutions to ensure data accuracy, freshness, and reliability.
Lead data modeling efforts to support business growth, ensuring scalability and performance.
Build and scale A/B testing frameworks to enable data-driven decision-making across the organization.
Collaborate with stakeholders to translate complex business requirements into scalable data solutions.
Mentor teams on data best practices and drive adoption of data-driven methodologies.
Requirements
5+ years of experience building and scaling data infrastructure in high-growth environments.
Proven experience in startup environments, with a track record of taking on multiple responsibilities and independently driving initiatives.
Deep expertise in modern data stack tools, particularly Snowflake and dbt.
Strong background in data modeling, schema design, and data architecture at scale.
Demonstrated experience implementing data quality frameworks and observability solutions.
Experience building and scaling experimentation (A/B testing) infrastructure.
Expert-level SQL skills and proficiency in Python.
Track record of successfully managing data infrastructure during periods of explosive growth.
A lean two-person data team requires resourcefulness and the ability to prioritize high-impact work.
Nice to have: experience with Snowflake, dbt, Rudderstack, Sigma Computing, Metaplane, and Eppo; blockchain or cryptocurrency experience; improving dashboard performance and optimizing queries at scale; implementing data cataloging and metadata management solutions.