{{Company name}} is looking for a Data Analyst to turn raw data into decisions. You will sit close to the business, answer real questions with well-built analysis, and give teams the dashboards and metrics they need to act with confidence.

What you'll do

• Partner with business stakeholders to frame vague questions as answerable analyses.
• Write clean, efficient SQL against our warehouse to explore and validate data.
• Build and maintain dashboards and self-serve reports that teams actually use.
• Define and document core metrics so the whole company counts things the same way.
• Run ad hoc deep dives on product, marketing, or operations questions and present clear recommendations.
• Check data quality at the source, flag gaps, and work with engineering to fix them.
• Communicate findings in plain language — the insight matters more than the chart.

What we're looking for

• {{Years of experience}} years of hands-on analytics experience in a data analyst or similar role.
• Strong SQL: joins, window functions, and query optimization are daily tools for you.
• Experience with at least one BI tool (for example a dashboarding platform your team relied on).
• Solid grounding in descriptive statistics and knowing when a difference is meaningful.
• The habit of sanity-checking numbers before anyone else has to.
• Clear written communication: your analyses end with a recommendation, not just a table.

Nice to have

• Python or R for analysis beyond what SQL handles well.
• Experience with dbt or another analytics-engineering workflow.
• Exposure to experimentation and A/B test analysis.
• Domain experience in {{Industry}}.

Compensation and benefits

• {{Salary range}}
• {{Benefits summary}}
• {{Location / remote policy}}

How to apply

{{Application instructions}} Include one example of an analysis that changed a decision — what the question was, what you found, and what happened next.