Business Data Analyst

About The Role

The role sits at the intersection of data engineering and business strategy — translating raw product, revenue, and operational data into models and dashboards that executives and product teams actually use to make decisions.

Working closely with data engineers and analytics engineers, the role owns the full analytics lifecycle: defining metrics with stakeholders, building reliable pipelines and semantic layers, and shipping analyses that change what the company builds next.

Key Responsibilities

• Build and maintain SQL models and dbt transformations powering core business metrics — retention, conversion, unit economics, and funnel performance
• Design and ship dashboards in Looker, Tableau, or Mode that give product and go-to-market teams self-serve access to trusted data
• Partner with stakeholders across product, finance, and operations to define metric definitions, instrument tracking plans, and scope analytical projects
• Run deep-dive analyses — cohort studies, A/B test evaluations, segmentation, and forecasting — using Python or R, and present findings to senior leadership
• Identify data quality issues at the source, partner with data engineers on pipeline fixes, and maintain documentation of metric logic and lineage
• Own experimentation analysis end-to-end: experiment design review, statistical significance testing, and post-launch readouts
• Contribute to the analytics codebase via version control (Git), code reviews, and reusable dbt packages and macros

What We Are Looking For

• 3–6 years of experience in data analytics, business intelligence, or analytics engineering roles
• Expert-level SQL — complex window functions, CTEs, query optimization — and hands-on experience with dbt or similar transformation frameworks
• Working proficiency in Python or R for data manipulation (pandas, polars) and statistical analysis
• Proven experience building executive-facing dashboards in Looker, Tableau, or Power BI, including semantic model design
• Strong statistical foundation: hypothesis testing, regression, cohort analysis, and experiment design
• Bachelor's degree in a quantitative field (statistics, economics, computer science, engineering) or equivalent practical experience
• Bonus: Experience with Snowflake/BigQuery at scale, exposure to event tracking tools (Segment, Amplitude), and familiarity with Airflow or Dagster