Data Analyst
Remote (United States)
Data Analyst
Employment Type: Full Time
Department: Finance
Annual Base Salary: $85,000–$100,000 per year
About the Role
The Data Analyst will be an early member of the Data & Analytics team, working closely with the Director of Data & Analytics to expand how data is used across the business to support decision-making.
This is a full-stack, cross-functional analytics role spanning data infrastructure, ingestion, modeling, transformation, analysis, business intelligence development, and direct stakeholder partnership. The position supports teams across Product Development, Marketing, direct-to-consumer operations, B2B, Finance, Operations, and Inventory Planning, with a focus on solving high-impact business problems and continuing to build the breadth and depth of the analytics function.
The current data environment includes Snowflake, Fivetran, dbt, Power BI, GitHub, SQL, R, and an increasing use of Python. AI-assisted development is a standard part of the team’s workflow. Much of the code is developed collaboratively with AI agents using tools such as Claude Code, then reviewed, tested, and refined. Prior expertise with AI development tools is not required, but strong data and modeling fundamentals, sound judgment, and curiosity about evolving analytics practices are important.
The role is best suited for someone who connects data findings to broader business needs, focuses on turning analysis into action, is comfortable solving both simple and complex problems, questions unclear metrics or assumptions, and is willing to handle practical day-to-day issues when needed. Strong technical fundamentals are essential, along with an eagerness to learn, good judgment in ambiguous situations, and a desire to improve how data is used across the organization.
What You’ll Do
- Partner directly with stakeholders across Product Development, Marketing, direct-to-consumer operations, B2B, Finance, Operations, and Inventory Planning to translate ambiguous business questions into clearly defined analyses, dashboards, and data products.
- Own analytics work from end to end, including scoping, building, validating, and communicating findings.
- Build and maintain dbt models that transform raw source-system data into reliable, well-documented datasets.
- Write tests and documentation that enable both team members and AI agents to confidently use downstream data assets.
- Develop and maintain semantic context, dashboards, and reports used by teams across the business for day-to-day decision-making.
- Own metric definitions and business semantics, helping stakeholders align when there are conflicting interpretations of definitions or numbers.
- Review, validate, and strengthen AI-generated SQL, dbt models, and Python code, identifying issues that may pass technical tests but remain incorrect from a business or data perspective.
- Collaborate with AI agents during code development while applying the data judgment needed to ensure output is accurate and trustworthy.
- Investigate complex or ambiguous data questions when answers are not immediately available in existing schemas.
- Work with source-system owners, investigate edge cases, reconcile conflicting definitions, and improve the organization’s understanding and representation of business data.
- Help build and maintain the data infrastructure, including Snowflake, Fivetran, dbt, GitHub, Power BI, R, and Python.
- Contribute to decisions about how the data and analytics technology stack should evolve over time.
- Improve data governance for both the Data & Analytics team and the broader business by creating useful documentation that can also serve as context for future AI-assisted work.
- Continuously develop technical and analytical skills as data analytics practices, technologies, and AI-assisted development continue to evolve.
Qualifications
Required Qualifications
- At least three years of professional experience as a data analyst, analytics engineer, or in a similar role.
- Advanced SQL skills, including experience with common table expressions, window functions, and complex real-world datasets.
- Ability to read and reason about SQL query plans well enough to identify potential issues or unexpected behavior.
- Hands-on experience with dbt, including creating models, tests, and documentation.
- Comfort contributing to an existing dbt project and an understanding of effective dbt development practices.
- Experience working with cloud data warehouses such as Snowflake, BigQuery, Databricks, Redshift, Microsoft Fabric, or similar platforms.
- Experience using Git and GitHub for version control as part of a regular development workflow.
- Development experience with at least one business intelligence platform such as Power BI, Tableau, Looker, Omni, or a similar tool.
- A practical understanding of AI-assisted development for analytics work, including its strengths, limitations, and the steps needed to ensure generated output is trustworthy.
- Demonstrated ability to build collaborative and trusting relationships with non-technical stakeholders.
- Ability to present findings clearly to leadership through verbal communication, written materials, and visual presentations.
Preferred Qualifications
- Working knowledge of Python and/or R for data analysis.
- Experience with one or more components of the current data stack, including Snowflake, Fivetran, dbt, GitHub, Power BI, Python, R, Claude Code, or Codex.
- Experience with systems such as NetSuite, Shopify, Google Analytics, Segment, or Klaviyo.
- Professional experience in a direct-to-consumer or omni-channel retail, apparel, footwear, or outdoor business.
- Experience working on a small or solo data team with end-to-end ownership of analytics work.
Benefits
- Medical coverage.
- Dental coverage.
- Vision coverage.
- Company-paid long-term disability coverage.
- Employee assistance programs.
- 401(k) plan with company match.
- Generous paid time off policies.
- Gear testing opportunities, employee perks, and additional benefits.
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