Data Analyst — San Francisco, CA

About The Role

The Data Analyst owns the analytical layer of a fast-moving product and growth organization - turning raw event data, warehouse tables, and product metrics into answers that drive roadmap and business decisions.

This is a hands-on role in the data itself. The analyst will work closely with data engineers on pipeline and data model design, and partner directly with product managers and go-to-market leaders to define metrics, build dashboards, and run rigorous analyses.

Key Responsibilities

• Build and maintain core dashboards and self-serve reporting in Looker (or equivalent BI tools) used daily by product, growth, and leadership teams

• Write advanced SQL against a cloud data warehouse (Snowflake, BigQuery, or Redshift) to model metrics and answer ad hoc analytical questions quickly and accurately

• Design and analyze experiments (A/B tests) end-to-end: define success metrics, compute sample sizes, run significance checks, and deliver clear readouts with recommendations

• Develop and document semantic layers and metric definitions, partnering with analytics engineers to keep dbt models consistent and trustworthy

• Perform deep-dive analyses on user behavior, funnel conversion, retention, and revenue drivers using SQL, Python, or R

• Partner with data engineers to improve data quality, instrument new event tracking, and identify gaps in the data pipeline

• Translate business questions into structured analytical frameworks and present findings to stakeholders in concise, decision-oriented narratives

What We Are Looking For

• 3–6 years of experience in data analytics, business intelligence, or product analytics at a technology company

• Expert-level SQL - complex joins, window functions, CTEs, and query optimization on large datasets

• Hands-on experience with at least one BI tool (Looker, Tableau, or Mode) and ownership of dashboards used by non-technical stakeholders

• Proficiency in Python or R for data manipulation and statistical analysis (pandas, numpy, scipy)

• Experience with cloud data warehouses (Snowflake, BigQuery, or Redshift) and modern data stack concepts (dbt, semantic metrics, data quality monitoring)

• Bachelor's degree in a quantitative field (Statistics, Economics, Computer Science, Engineering) or equivalent practical experience

• Bonus: experience designing experimentation platforms, building cohort/retention models, working with product analytics tools (Amplitude, Mixpanel), or contributing to dbt/semantic layer development