Business Data Analyst

About The Role The Business Data Analyst sits at the intersection of data infrastructure and business decision-making: translating raw pipeline outputs into reliable metrics, dashboards, and analyses that leadership actually uses to steer the company. You will work closely with data engineers, product managers, and go-to-market teams, owning the semantic layer and reporting stack while identifying where data quality, instrumentation, or analysis needs improvement. Key Responsibilities Build and maintain core business metrics (retention, funnel conversion, unit economics) using SQL against the warehouse (Snowflake, BigQuery, or Redshift)Develop and own dashboards in Looker, Tableau, or dbt-generated reporting layers used by product, sales, and executive teamsPartner with data engineers to design data models and dbt transformations that make analytics self-serve and trustworthyRun deep-dive analyses on user behavior, revenue drivers, and operational efficiency, communicating findings with clear written narratives and visualizationsPartner with product managers to define experiment metrics, review A/B test results, and flag statistical red flagsAudit and improve data quality: build anomaly detection checks, resolve metric discrepancies, and document metric definitionsAdvocate for and drive adoption of self-serve analytics tooling across non-technical stakeholders What We Are Looking For 3–6 years of experience in data analytics, business intelligence, or analytics engineering at a product-driven technology companyExpert-level SQL: window functions, CTEs, query optimization on large datasetsHands-on experience with a modern data stack: dbt, Snowflake/BigQuery, and a BI tool (Looker, Tableau, or Mode)Strong proficiency in Python (pandas) or R for ad hoc analysis and statistical workA track record of translating ambiguous business questions into concrete, measurable analysesBachelor's degree in a quantitative field (statistics, economics, CS, engineering) or equivalent practical experienceBonus: experience with A/B testing frameworks, Python data visualization (Plotly, Streamlit), or building metrics layers / semantic models