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. Knowing what a trial start actually counts, why tracked revenue and realized revenue are different, how store refunds land in our data, and which model answers a question correctly the first time. That knowledge is what turns a half-formed Slack question into a number someone can act on within the hour.
So you’ll spend most of your time with business teams: understanding what they’re trying to decide, turning vague questions into analysis, and shipping the datasets and dashboards they rely on. You’ll build that domain knowledge fast, working day to day with the person who currently owns Analytics here. He’ll be your closest partner and the person who helps you grow into the domain.
The second thing that makes this role exciting is how we expect you to work. We’re building the infrastructure that lets AI agents access our data safely, and agentic tooling that answers questions grounded in our semantic layer rather than guessing. You’ll be one of its heaviest users and one of the people who makes it trustworthy: curating the semantic context, catching the answers that look right and aren’t, and pushing definitions back into dbt and LookML where they belong. We’re not hiring someone to do the same volume of work faster, we’re hiring someone who supports multiple teams well using this collection of new tools as a force multiplier.