Data Analyst

About The Role

The Data Analyst role is responsible for bridging the gap between raw data and strategic decision-making by delivering high-impact analytics, automated reporting, and actionable business insights. This position operates at the intersection of product, engineering, and operations, ensuring that stakeholders have access to reliable metrics to evaluate growth and product performance.

The role involves navigating complex data environments to identify trends, diagnose anomalies, and forecast future outcomes. Success in this position requires a blend of technical data manipulation skills and the ability to translate technical findings into clear, executive-level narratives.

Key Responsibilities

• Design, build, and maintain automated dashboards in Tableau, Looker, or Mode that track core KPIs and operational health for cross-functional teams
• Execute complex SQL queries across large-scale data warehouses like Snowflake, BigQuery, or Redshift to extract and transform data for ad-hoc analysis
• Partner with product managers to design A/B tests, define success metrics, and perform post-launch statistical analysis to measure feature impact
• Collaborate with data engineers to define data requirements and schemas, ensuring the underlying data infrastructure supports accurate and performant reporting
• Develop and document data models within the analytics layer using dbt or similar transformation tools to maintain a single source of truth
• Conduct deep-dive exploratory analyses to identify root causes of business trends and present findings to leadership through data storytelling

What We Are Looking For

• 2–4 years of experience in data analytics, business intelligence, or a similar quantitative role within a high-growth technology environment
• Advanced proficiency in SQL, including window functions, complex joins, and query optimization for large datasets
• Hands-on experience with at least one major BI tool such as Looker (LookML), Tableau, or Sigma
• Foundational knowledge of Python or R for data manipulation, statistical analysis, and basic automation tasks
• Strong understanding of statistical concepts related to hypothesis testing, experiment design, and probability
• Bachelor’s degree in a quantitative field such as Mathematics, Statistics, Computer Science, Economics, or Physics
• Bonus: Experience with dbt, Airflow, or specialized product analytics tools like Mixpanel or Amplitude