Business Data Analyst

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