The mission of the Staff Analytics Engineer at Cozey
As Staff Analytics Engineer reporting to Frank Joly, Director of Data Engineering, your mission is to own and scale Cozey’s analytics engineering foundation — building the data models, pipelines, and frameworks that power business decisions across the organization. You will set the technical standard for how data is structured, documented, and trusted, enabling every team to move faster with confidence.
What you’ll be doing
- Design, build, and maintain scalable dbt data models that serve as the single source of truth for key business metrics across the organization.
- Define and enforce analytics engineering best practices: naming conventions, testing frameworks, documentation standards, and modular design patterns.
- Partner with business stakeholders to deeply understand business processes, translating them into properly modeled, reliable, and performant data assets that accurately reflect how the business operates.
- Lead the architecture and governance of Cozey’s data warehouse (e.g. Snowflake), including schema design, access controls, and cost optimization.
- Identify and resolve data quality issues proactively; build automated testing and monitoring to ensure pipeline reliability.
- Mentor junior and intermediate data team members, conducting code reviews and raising the overall technical bar of the team.
- Drive the roadmap for analytics infrastructure improvements, balancing technical debt with new capabilities.
We’d love to hear from you if you have
- 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: you’re able to explain technical concepts to non-technical stakeholders.
- A track record of ownership: you’ve led data initiatives end-to-end, not just contributed to them.
We care about you