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

Requirements

5+ years of experience in analytics engineering, data engineering, or similar roles
Hands-on experience modeling subscription or usage-based revenue, ideally using Stripe
Proven ownership of financial or investor-facing metrics implemented in code (not spreadsheets)
Advanced SQL and dbt experience in a modern data warehouse such as Snowflake
Experience reconciling modeled outputs to source systems and financial reports
Comfortable partnering directly with Finance and owning the technical implementation of their definitions
Strong discipline around testing, documentation, and maintainability

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

SQLdbtdata modelingrevenue modelingfinancial metricsdata reconciliationperformance optimizationtestingdocumentationanalytics engineering

Soft Skills

collaborationproblem-solvingattention to detailcommunicationownershipdisciplineengineering judgmentadaptabilityorganizational skillsstakeholder management