Data Analyst

About The Role

The role drives the design, development, and maintenance of scalable business intelligence solutions and analytical models that empower product and operations teams to make data-backed decisions. This position sits at the intersection of business strategy and data engineering, translating raw transactional data into actionable, high-impact insight pipelines.

The analyst will collaborate closely with product managers, data engineers, and executive stakeholders to define key performance indicators, build self-service reporting infrastructure, and perform deep-dive exploratory analysis on user behavior and system performance.

Key Responsibilities

• Design, build, and maintain production-ready dashboards and data visualizations in Tableau or Looker to track core business metrics
• Write complex, highly optimized SQL queries to extract and aggregate multi-terabyte datasets from Snowflake or BigQuery data warehouses
• Develop and maintain dbt (data build tool) models to transform raw data into clean, documented, and tested analyst-ready schemas
• Conduct deep-dive exploratory data analysis to identify product optimization opportunities, diagnose performance anomalies, and support strategic planning
• Design and analyze A/B tests to measure the impact of new product features and marketing campaigns on user retention and conversion metrics
• Partner with data platform engineers to improve data quality, schema designs, and data ingestion pipelines across critical business applications

What We Are Looking For

• 3–6 years of experience as a Data Analyst, Analytics Engineer, or in a similar quantitative role within a modern data stack ecosystem
• Advanced proficiency in SQL, including window functions, CTEs, query optimization, and schema design
• Hands-on experience with modern BI tools (Tableau, Looker, or PowerBI) and data transformation frameworks (dbt)
• Strong foundational knowledge of statistical concepts, including hypothesis testing, sample size determination, and regression analysis
• Bachelor's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or equivalent practical experience
• Bonus: Experience with Python or R for data manipulation (pandas, numpy) and automated ETL scripting