Data Analyst

Stio

Data Analyst supporting data-driven decisions for Stio, an omni-channel mountain brand. Collaborating across departments and utilizing advanced analytics tools for impactful business insights.

Posted 6/5/2026full-timeRemote • Colorado, Utah, Wyoming • 🇺🇸 United StatesMid-LevelSenior💰 $85,000 - $100,000 per yearWebsite

Tech Stack

Tools & technologies

Amazon RedshiftBigQueryCloudPythonSQLTableau

About the role

Key responsibilities & impact

Partner directly with stakeholders across the business (Product Development, Marketing, DTC, B2B, Finance, Operations, Inventory Planning) to translate ambiguous questions into well-defined analyses, dashboards, and data products. You’ll own these end-to-end: scoping, building, validating, and communicating findings.
Build and maintain dbt models that turn raw source-system data into trustworthy, well-documented datasets. Write the tests and documentation that let both humans and AI agents downstream rely on the work.
Develop and maintain the semantic context, dashboards, and reports that the rest of the business uses to operate day-to-day.
Own metric definitions and business semantics. Drive alignment when stakeholders disagree on what a definition or number means.
Review and harden AI-generated SQL, dbt models, and Python code with the judgment to catch issues that pass tests but are semantically wrong. The majority of your output will be code you’ve collaborated on with AI agents, and you’ll bring the data intuition that makes that work trustworthy.
Investigate ambiguous data questions where the answer isn’t in the schema: talk to source-system owners, investigate edge cases, reconcile conflicting definitions, and improve our model of the business.
Help build and maintain Stio’s data infrastructure — currently Snowflake, Fivetran, dbt, GitHub, Power BI, R, and Python — and contribute to decisions about where the stack should evolve.
Improve data governance for both the Data & Analytics team and the business at large by creating documentation that’s actually useful and that AI agents can consume as context for future work.
Continuously develop your skills as the practice of data analytics evolves. This is a real part of the job, not something done on the side.

Requirements

What you’ll need

3+ years of professional experience as a data analyst, analytics engineer, or similar role
Advanced SQL: CTEs, window functions, comfortable wrangling messy real-world data, can read and reason about query plans well enough to know when something is off
Hands-on experience with dbt, including writing models, tests, and documentation. You don’t need to have built a dbt project from scratch, but you should be comfortable contributing to one and know what good looks like
Experience with cloud data warehouses (Snowflake, BigQuery, Databricks, Redshift, Microsoft Fabric, or similar)
Version control with Git/GitHub as part of your normal workflow
Experience as a developer with at least one BI tool (Power BI, Tableau, Looker, Omni, or similar)
A real point of view on AI-assisted development for analytics work — what it’s actually good at, where it falls down, what you do to make the output trustworthy
History of building collaborative, trusting relationships with non-technical stakeholders
Comfort presenting findings to leadership verbally, in writing, and visually

Benefits

Comp & perks

Medical, Dental Vision plans
Company Paid Long Term Disability
Employee Assistance Programs
401k with Match
Generous paid time off policies
Gear test, perks and more

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

SQLdbtdata modelingdata validationdata analysisAI-assisted developmentdata governancedata wranglingreportingdata documentation

Soft Skills

stakeholder managementcommunicationcollaborationproblem-solvingrelationship buildingpresentation skillscritical thinkingdata intuitionalignment facilitationadaptability