About The Role
The role sits at the intersection of data infrastructure and business decision-making - building reliable pipelines, owning core reporting, and translating messy business questions into trustworthy analyses that leadership actually uses.
The analyst will work with a modern data stack (Snowflake, dbt, Python) and partner directly with product, finance, and go-to-market teams to define metrics, pressure-test assumptions, and surface insights that drive roadmap and revenue decisions.
Key Responsibilities
Design, build, and maintain reliable data pipelines in Python and SQL, orchestrating workflows with Airflow and monitoring for data quality and freshness
Develop and maintain dbt models and data marts in Snowflake, ensuring consistent metric definitions across teams
Own key business dashboards and reporting in Looker or Tableau - from KPI definition to ongoing maintenance and stakeholder training
Run deep-dive analyses (cohorting, funnel analysis, A/B test evaluation, unit economics) that directly influence product and pricing decisions
Partner with finance and operations to build forecasting models and track performance against plan
Define, document, and champion data governance standards: naming conventions, metric definitions, and semantic layers
Present findings clearly to both technical and executive audiences, with actionable recommendations
What We Are Looking For
3–6 years of experience in business analytics, data analysis, or analytics engineering at a technology company
Expert-level SQL and strong Python (pandas, matplotlib); comfort working with large, complex datasets
Hands-on experience with cloud data warehouses (Snowflake, BigQuery, or Redshift) and transformation tools (dbt)
Experience building dashboards and reporting in Looker, Tableau, or Power BI
Strong grasp of statistics: hypothesis testing, significance, regression basics, and common analytical pitfalls
Bachelor's degree in a quantitative field (economics, statistics, engineering, computer science) or equivalent practical experience
Bonus: Experience with Airflow or Dagster, experimentation platforms, reverse ETL tools (Hightouch, Census), or a background in SaaS metrics and ARR analytics