[Hiring] Data Analyst @RevenueCat

Role Description

We're hiring a Data Analyst to work as close as possible to the teams that run RevenueCat's business, including Marketing, Sales, Finance, People, Ops, Product, etc.

• The most valuable thing on our Analytics team today isn't SQL, it's domain knowledge.
• Understanding trial starts, tracked revenue vs realized revenue, store refunds, and correct models is crucial.
• Spend most of your time with business teams to understand their decisions and turn vague questions into analysis.
• Build domain knowledge quickly by working day to day with the current Analytics owner.
• Work with AI agents and agentic tooling to ensure trustworthy data access.
• Curate semantic context, catch incorrect answers, and push definitions into dbt and LookML.

What you will do

• Partner regularly with Marketing, Sales, Finance, and Product teams to learn their goals and metrics.
• Own analysis end to end: clarify questions, build or select datasets, deliver answers, and ensure decisions follow.
• Document subscription domain knowledge: metric definitions, caveats, filters, and known issues.
• Build trusted analytics assets: models in dbt, explores in LookML, and reliable dashboards.
• Use agent tooling effectively and contribute back to it by feeding semantic context and flagging wrong answers.
• Contribute to the data platform by making small model and pipeline improvements and debugging discrepancies.
• Translate business context into robust analysis and data reality into understandable language for non-technical stakeholders.

Qualifications

• 3+ years in an analytics role (Data Analyst, BI Analyst, Business Analyst, Analytics Engineer or similar).
• Experience as the direct analytics partner to a business team such as Marketing, Sales, or Finance.
• Curiosity: uncomfortable without understanding numbers, digging until clarity is achieved.
• Ability to ask the question behind the question and learn new domains over new tools.
• Comfortable creating structure without fully formed requirements.
• Focus on being useful and clear rather than polished dashboards.
• Desire to be a partner to the business, not just a request queue.

Requirements

• Strong SQL skills and comfort working directly in a warehouse.
• Experience owning datasets and dashboards relied upon by non-technical teams.
• Familiarity with version-controlled environments: git, branches, pull requests, code review.
• Experience working with AI agents and a skeptical approach to their outputs.
• Clear written communication, especially regarding limits, caveats, and what numbers do not convey.

Nice to have, and genuinely not required

• Python, dbt, Looker or LookML, Snowflake or ClickHouse experience.
• Subscription or fintech domain experience.
• Experience with high-volume data.

Benefits

• Competitive equity in a fast-growing, Series C startup backed by top-tier investors, including Y Combinator.
• 10-year window to exercise vested equity options.
• Fully remote and flexible work environment.
• 4-5 weeks of suggested time off annually for mental, physical, and emotional recharge.
• $2,000 USD for workspace setup and $1,000 USD annual stipend for continuous learning.