The Lead Analytics Engineer will model revenue, specifically subscription revenue, manage financial KPIs, and ensure reconciliation with source systems like Stripe, while adhering to data governance standards.
About HighLevel:
HighLevel is an AI powered, all-in-one white-label sales & marketing platform that empowers agencies, entrepreneurs, and businesses to elevate their digital presence and drive growth. We are proud to support a global and growing community of over 1 million businesses, comprised of agencies, consultants, and businesses of all sizes and industries. HighLevel empowers users with all the tools needed to capture, nurture, and close new leads into repeat customers. As of mid 2025, HighLevel processes over 4 billion API hits and handles more than 2.5 billion message events every day. Our platform manages over 470 terabytes of data distributed across five databases, operates with a network of over 250 microservices, and supports over 1 million hostnames.
Our People
With over 1,500 team members across 15+ countries, we operate in a global, remote-first environment. We are building more than software; we are building a global community rooted in creativity, collaboration, and impact. We take pride in cultivating a culture where innovation thrives, ideas are celebrated, and people come first, no matter where they call home.
Our Impact
As of mid 2025, our platform powers over 1.5 billion messages, helps generate over 200 million leads, and facilitates over 20 million conversations for the more than 1 million businesses we serve each month. Behind those numbers are real people growing their companies, connecting with customers, and making their mark - and we get to help make that happen.
About the Role:
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.
You will operate within the architectural and governance standards defined by the Analytics Engineering team, while owning the Revenue domain as an execution and implementation leader. Your work will directly power ARR, MRR, NRR, churn, customer counts, and other metrics used in executive reporting and external disclosures.
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
Requirements:
- 7+ 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
Success in this role looks like:
- Stripe revenue data is modeled once and reused everywhere
- ARR, MRR, NRR, and churn are produced by tested dbt models that reconcile to source systems
- Revenue models are reliable, governed, and safe to evolve over time
- Finance and Analytics depend on the data platform as the single source of truth for revenue metrics
EEO Statement:
The company is an Equal Opportunity Employer. As an employer subject to affirmative action regulations, we invite you to voluntarily provide the following demographic information. This information is used solely for compliance with government recordkeeping, reporting, and other legal requirements. Providing this information is voluntary and refusal to do so will not affect your application status. This data will be kept separate from your application and will not be used in the hiring decision.
#LI-Remote #LI-NJ1
Top Skills
Dbt
Snowflake
SQL
Stripe
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