As a Lead Analytics Engineer focused on Revenue & Financial Modeling, you will own the end-to-end modeling of subscription revenue and financial KPIs. You will work closely with Finance to translate business definitions into precise, testable logic, and you will be accountable for ensuring those outputs reconcile to source systems such as Stripe.

Responsibilities:

• Design and maintain the canonical revenue and subscription data model, centered on Stripe
• Model subscription lifecycles including upgrades, downgrades, renewals, cancellations, refunds, and disputes
• Implement ARR, MRR, NRR, churn, and customer/account counts as tested, versioned dbt models
• Partner with Finance to translate business definitions into precise, production-grade SQL logic
• Build and maintain reconciliation logic between dbt models, Stripe, and Finance-owned reports
• Investigate and resolve discrepancies surfaced during reconciliation and downstream use
• Own the technical correctness of revenue numbers used in executive and external reporting
• Own data quality for all revenue and financial models, including test coverage and issue investigation
• Ensure revenue models adhere to Analytics Engineering standards for documentation, lineage, ownership, and catalog synchronization
• Participate in governed change workflows for critical revenue assets, ensuring changes are reviewed, traceable, and auditable
• Apply sound engineering judgment when balancing correctness, reliability, and delivery speed
• Establish a durable revenue and KPI foundation in the near term
• As the foundation stabilizes, improve performance, maintainability, and usability of revenue models
• Over time, support forecasting, cohort analysis, and advanced revenue analytics, and contribute revenue-domain expertise to broader Analytics Engineering initiatives
• Work closely with Finance as the technical owner of revenue modeling
• Coordinate with Data Engineering on ingestion, backfills, and schema changes across Stripe and other revenue-related source systems
• Support BI and Analytics teams to ensure revenue models are usable and performant