Data Analyst

Quick Facts

• Role: Data Analyst

Description

Collaborate with Product, Growth, Finance, and Operations leadership to identify trends, diagnose churn and growth drivers, and uncover high-value business opportunities. Build clean, modular, version-controlled SQL models (e.g., with dbt) and create decision-focused dashboards and narrative reports using tools like Looker, Metabase, Tableau, or Power BI. Maintain data definitions and governance standards, and use AI-assisted analytics workflows and automated pipelines for faster exploration and real-time operational alerts.

Responsibilities

• Generate insights and support business strategy by partnering cross-functionally to spot trends and drivers
• Develop analytics engineering workflows, transforming raw data into production-ready tables
• Design intuitive dashboards and narrative reporting that drive decisions
• Establish data quality, definitions, documentation, testing, and reliability standards
• Leverage AI-assisted analytics and automated pipelines for real-time alerting

Requirements

• 2–5 years of experience in data analytics, product analytics, or business intelligence
• Strong SQL skills, including window functions, CTEs, and performance optimization
• Familiarity with modern data transformation and analytics engineering practices
• Hands-on experience with cloud data warehouses such as Snowflake, BigQuery, or Databricks and BI/semantic layer tools
• Ability to translate complex findings into actionable recommendations for non-technical stakeholders
• Solid understanding of basic statistics (hypothesis testing, confidence intervals, regression)
• Basic knowledge of Git/GitHub workflows for managing analytics code

Benefits

• Opportunity to partner with cross-functional leadership and drive strategy with data insights
• Build and ship production-ready analytics models, dashboards, and automated alerting workflows