Staff Analytics Engineer

6d6 days ago

Cozey

CA · Full-time · $200,000 – $280,000

About this role

At Cozey, we’re empowering possibilities in your home and making furniture shopping easy and enjoyable. Our stylish furnishings adapt to evolving lifestyles, combining innovation with great value and customer service. As a fast-growing online-first brand, our success is driven by a passionate team redefining the furniture experience.

As Staff Analytics Engineer reporting to the Director of Data Engineering, own and scale Cozey’s analytics engineering foundation. Build data models, pipelines, and frameworks powering business decisions organization-wide. Set the technical standard for structured, documented, and trusted data enabling teams to move faster.

Design and maintain scalable dbt data models as the single source of truth for key metrics. Partner with stakeholders to translate business processes into reliable data assets. Lead data warehouse architecture including schema design, access controls, and cost optimization.

Proactively identify data quality issues with automated testing and monitoring. Mentor junior data team members via code reviews to raise the technical bar. Drive the roadmap for analytics infrastructure improvements balancing technical debt and new capabilities.

Requirements

6+ years of experience in analytics engineering, data engineering, or a closely related field
Deep expertise with DBT in a production environment, including macros, tests, and model documentation
Strong SQL skills and experience working with cloud data warehouses
Demonstrated ability to design and implement scalable dimensional data models
Capability with ingestion tools (e.g. Fivetran, Airbyte, Funnel)
Experience with orchestration tools (e.g. StepFunction, Airflow, Dagster)
Familiarity with Python for data pipeline tasks or analytics automation
Strong communication skills to explain technical concepts to non-technical stakeholders

Responsibilities

Design, build, and maintain scalable dbt data models that serve as the single source of truth for key business metrics
Define and enforce analytics engineering best practices: naming conventions, testing frameworks, documentation standards, and modular design patterns
Partner with business stakeholders to understand processes and translate them into modeled, reliable data assets
Lead the architecture and governance of Cozey’s data warehouse including schema design, access controls, and cost optimization
Identify and resolve data quality issues proactively; build automated testing and monitoring for pipeline reliability
Mentor junior and intermediate data team members, conducting code reviews and raising the technical bar
Drive the roadmap for analytics infrastructure improvements, balancing technical debt with new capabilities