Job Description

Responsibilities:

Partner with stakeholders to understand data needs and translate business questions into technical requirements for data models, pipelines, dashboards, and self-service tools.
Design, build, document, and maintain reliable data pipelines using dbt, Dagster, Redshift, and related tools.
Transform raw data into trusted, canonical datasets for reporting, analysis, experimentation, and decision-making.
Build high-performance dashboards and analytical tools in Hex, Tableau, or similar platforms.
Use AI tooling to accelerate pipeline development, SQL/dbt work, and documentation.
Partner with data scientists, analysts, and engineers to bridge business needs and data infrastructure.

Requirements:

5+ years of experience in analytics engineering, data engineering, or business intelligence, ideally in a fast-paced, high-growth environment.
Strong SQL skills, including experience with large datasets, complex transformations, and performance optimization.
Hands-on experience designing and maintaining reliable data pipelines using modern tools such as dbt, Dagster, Redshift, or equivalent.
Proficiency in a scripting language; Python preferred.
Demonstrated use of AI in your day-to-day workflow — LLM-assisted coding or prompt-driven data exploration.
Experience building dashboards and analytical tools in Hex, Tableau, or comparable BI/reporting platforms.
Strong understanding of data modeling, metric design, and analytics engineering best practices.
Strong communication skills, with a bias toward clear documentation, reliable systems, and measurable business impact.

Benefits & Perks: