Data Analyst

About The Role

The role serves as the analytical engine driving strategic decisions across product, engineering, and operations teams. This position is responsible for transforming raw transactional and behavioral data into actionable dashboards, structured metrics, and deep behavioral insights.

The position sits within a centralized data team, collaborating closely with business stakeholders to define key performance indicators, design complex SQL queries, and build robust visualization layers that track the health of core business funnels.

Key Responsibilities

• Design, develop, and maintain automated business intelligence dashboards and operational reports using Tableau, Looker, or Power BI
• Write complex, optimized SQL queries to extract, transform, and analyze large-scale datasets from cloud data warehouses like Snowflake, BigQuery, or Redshift
• Perform deep-dive exploratory data analysis to identify product friction points, user retention cohorts, and conversion funnel bottlenecks
• Partner with data engineers to define requirements for clean, structured data models and upstream schema modifications
• Establish reliable data quality checks and validation frameworks to ensure high confidence and accuracy across all external and internal reporting assets
• Formulate and execute structured A/B testing frameworks, including sample size determination, statistical significance calculations, and post-experiment readouts

What We Are Looking For

• 2-4 years of experience as a data analyst, business intelligence analyst, or in a highly quantitative analytical role
• Advanced, production-level SQL skills, including expert proficiency with window functions, complex joins, and query optimization
• Hands-on experience building intuitive data visualizations and semantic layers in Looker (LookML) or Tableau
• Solid understanding of statistical concepts, hypothesis testing, regression analysis, and product analytics methodology
• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a related quantitative field
• Bonus: Experience writing Python or R for data manipulation (pandas, numpy), and familiarity with dbt (data build tool) or git workflows