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About the Role

We’re looking for a Data Analyst to help drive better decisions across the company through thoughtful analysis, clear metric definitions, and strong partnership with cross-functional teams.

In this role, you’ll work closely with Product, Engineering, Operations, and GTM teams to answer high-impact business questions. You’ll translate ambiguity into structured analysis, uncover insights that shape strategy, and ensure our metrics are accurate and trustworthy.
While this role is business-impact focused, you’ll also contribute to building and maintaining clean analytical data models that support scalable, reliable reporting.
You’ll join a small, high-impact data team where ownership is real and your work will directly influence how we grow.

What You'll Do

Partner cross-functionally to define KPIs, answer strategic questions, and support decision-making.

Build reporting and dashboards that drive action — not just monitoring.

Present insights clearly to both technical and non-technical stakeholders.

Perform data analysis to uncover trends, risks, and growth opportunities.

Define and maintain core business metrics to ensure alignment across teams.

Support and improve dimensional data models (fact and dimension tables) in the warehouse.

Build and maintain reliable data transformations to ensure accuracy and consistency.

Help improve data quality, documentation, and reporting standards.

Contribute to forecasting, experimentation analysis, and predictive or inference modeling initiatives.

What We're Looking For
Must-Have

2–4 years of experience in a Data Analyst, Analytics Engineer, or similar role.

Strong SQL skills and experience working in a modern cloud data warehouse.

Experience performing exploratory analysis and communicating actionable insights.

Experience working cross-functionally and influencing business stakeholders.

Demonstrated ability to drive measurable impact through data.

Experience building analytical data models — not only dashboards and ad hoc analysis.

Strong written and verbal communication skills.

A proactive mindset and willingness to take on projects outside your comfort zone.

Familiarity with tools such as:

Fivetran, Airbyte, Stitch (or similar ingestion tools)

dbt, SQLMesh, or dataform

A modern BI tool (Tableau, Sigma, Looker, etc)

We currently use Airbyte, BigQuery, SQLMesh, Looker Studio, etc

Familiarity with version-controlled analytics workflows.

Familiarity with dimensional modeling concepts (fact tables, dimension tables, star schemas).

Nice-to-Have

Experience building predictive or inference models.

Experience building and maintaining data ingestion pipelines.

Experience implementing data quality testing and documentation practices.

Experience working with GTM teams to define and report on GTM metrics.

Exposure to event-based or product analytics data.

Experience using AI effectively in your own workflow.

Qualifications

BS in Computer Science, Statistics, Data Science, Mathematics, Engineering, or a related quantitative field (or equivalent practical experience).

2–4 years of relevant professional experience in analytics.

Proficiency in SQL required; experience with modern analytics tooling strongly preferred.

Demonstrated experience working cross-functionally with Product, Engineering, Customer Success, or business stakeholders.