Data Analyst

About RevenueCat

RevenueCat simplifies the complexity involved in building and scaling in-app subscriptions. Since its participation in Y Combinator's Summer 2018 batch, it has become the leading monetization platform for mobile apps, powering over 40% of new subscription apps. The platform manages over $12 billion in annual purchase volume and supports a diverse customer base, from individual developers to major teams like OpenAI's mobile unit.

The company operates with over 150 remote employees across more than 25 countries, guided by core principles such as Customer Obsession, Continuous Delivery, Ownership, and Work-Life Balance. Joining the team means contributing to products used by hundreds of millions globally, helping developers increase their revenue.

Role Overview

The Data Analyst position operates closely with multiple RevenueCat teams including Marketing, Sales, Finance, People Operations, and Product. The role demands deep domain knowledge to transform ambiguous business queries into actionable insights rapidly. Emphasizing collaboration, the analyst will work alongside the current Analytics lead to develop expertise in subscription-related metrics, data discrepancies, and analytic methods.

The role also involves utilizing and enhancing advanced AI-based analytics tools that retrieve data securely and reliably. This includes curating semantic data context, validating AI-generated responses, and maintaining analytic definitions in platforms like dbt and LookML. The goal is not merely to accelerate analysis but to multiply impact by supporting several teams simultaneously with these innovative tools.

Responsibilities

• Collaborate regularly with business units such as Marketing, Sales, Finance, and Product to understand their objectives and the decisions they face.
• Take ownership of analyses by clarifying questions, selecting or constructing appropriate datasets, delivering insights, and ensuring results inform decision-making.
• Develop comprehensive documentation of domain knowledge including metric definitions, constraints, standard filters, and known data quirks, ensuring this knowledge is scalable.
• Create and maintain trustworthy analytical assets including dbt models, LookML explores, and dashboards that stakeholders can rely on without prior approval.
• Leverage and contribute to agentic AI tools by providing semantic context, identifying inaccuracies, and strengthening data definitions.
• Support and improve the data platform as needed by making small model or pipeline adjustments, troubleshooting issues, and resolving discrepancies.
• Translate complex data insights into terminology understandable to non-technical stakeholders and convey business requirements back into data-driven analysis.

Qualifications and Skills

• Minimum of three years experience in analytical roles such as Data Analyst, BI Analyst, Business Analyst, or Analytics Engineer, especially as an analytics partner to business functions like Marketing, Sales, or Finance.
• A strong sense of curiosity and investigative mindset to understand why data behaves as it does, asking deeper questions beyond initial dashboards.
• Motivated to learn new business domains over tools, comfortable working amidst evolving or incomplete requirements, and aiming to be a proactive and useful business partner rather than a task responder.
• Proficient in SQL with hands-on experience in working directly within data warehouses to independently extract insights.
• Experience managing analytical datasets and dashboards actively used by non-technical teams.
• Familiarity with version control systems such as git including branch workflows, pull requests, and code reviews, with analytics code managed in dbt and LookML repositories rather than ad hoc queries.
• Regular user of AI assistant tools with a critical approach to verifying outputs and providing clear explanations of data limitations and caveats.
• Excellent written communication skills tailored to explaining data insights, their constraints, and implications clearly and accurately.
• Preferred but not mandatory: knowledge of Python, dbt, Looker/LookML, Snowflake or ClickHouse, experience with subscription or fintech domains, and managing high-volume data pipelines.

Compensation and Benefits

• Competitive equity package in a fast-growing, Series C funded startup supported by prestigious investors including Y Combinator.
• 10-year timeframe to exercise vested equity options, allowing long-term value realization.
• Fully remote and flexible working conditions enabling work from various locations worldwide.
• Recommended 4-5 weeks of annual leave to support mental, physical, and emotional well-being.
• $2,000 USD setup allowance for home workspace and $1,000 USD yearly stipend dedicated to continuous learning and professional growth.