Data Analyst

About The Role

The role owns the analytical infrastructure and insights engine, turning raw event data and financial metrics into actionable strategic decisions for cross-functional leadership.

The analytics team works closely with data engineering and product management to build scalable semantic layers, interactive dashboards, and robust cohort models that drive user retention and growth.

Key Responsibilities

• Design and maintain clean, scalable data models in Snowflake or BigQuery using dbt to support company-wide reporting and metric definitions
• Write complex, highly optimized SQL queries to extract data, perform cohort analyses, and evaluate product feature adoption
• Build and maintain executive-facing dashboards and self-serve reporting views using Looker, Tableau, or Preset
• Partner with product managers and engineers to define telemetry requirements, tracking plans, and KPIs for new releases
• Conduct deep-dive exploratory data analyses to identify key growth levers, drop-off points, and monetization opportunities
• Establish rigorous data quality checks and anomaly detection pipelines to ensure absolute trust in core reporting metrics
  
  

What We Are Looking For

• 3–6 years of experience in data analysis, business intelligence, or analytics engineering within a high-growth technology company
• Advanced SQL proficiency: window functions, CTEs, performance tuning, and complex joins over large-scale datasets
• Hands-on experience with modern data stack tooling: dbt, Snowflake or BigQuery, and BI tools such as Looker or Tableau
• Strong foundation in statistics: hypothesis testing, experimental design, A/B testing evaluation, and segmentation analysis
• Demonstrated ability to translate ambiguous business problems into structured analytical frameworks and clear recommendations
• Bonus: Python proficiency for data manipulation (pandas), experience with event-tracking schemas (Segment/Amplitude), and bachelor's degree in a quantitative field