Revenue Analytics Engineer

About Lansweeper

Lansweeper is a leading IT asset management company that helps organizations gain complete visibility into their IT landscape. Our technology discovers, inventories, and manages every IT asset across on-premises, cloud, and IoT environments. As we grow through new products and market expansion, revenue analytics is becoming critical to steer the business forward.

• C-level decisions to optimize growth are based on revenue metrics and insights, as they are highly trusted facts on the evolution of the business.
• Revenue metrics are structured so they are relevant for board-level insights.
• Key trends in revenue metrics are explained by linking back to sales and finance processes, ensuring the right strategic decisions for growing the company are taken.
• Forecasting for key revenue metrics is in place and used to steer go-to-market actions.

• The sales organization is moving quickly and needs revenue facts to understand the success of its campaigns and to plan new sales plays.
• The market is changing and so is our product — we need to allocate sales and marketing efforts where it matters most for growth.
• Revenue metrics are sourced from multiple systems, have historic complexity due to acquisitions and system migrations, and data quality varies over time.

• Build, maintain, and improve the revenue data models that power executive-level reporting and board-ready metrics.
• Reconcile revenue data across systems of record (CRM, billing, ERP) and ensure a single source of truth for financial KPIs.
• Design and deliver dashboards and reports that translate complex revenue data into clear, actionable insights for sales, finance, and leadership.
• Partner with sales operations and finance to understand changing business processes and reflect them accurately in revenue analytics.
• Develop and maintain forecasting models for key revenue metrics to support go-to-market planning.
• Investigate and explain trends, anomalies, and shifts in revenue data, linking them back to underlying business drivers.
• Proactively improve data quality and integrity across revenue-related data pipelines.

• Experience with financial metrics reporting — you know how revenue, bookings, churn, and related KPIs are defined and measured.
• Understanding of subscription sales processes — you are familiar with concepts like ARR, MRR, expansion, contraction, and renewal cycles.
• Strong SQL skills — you can write, optimize, and debug complex queries against large datasets.
• Experience in reconciling systems of record — you have dealt with data mismatches between CRM, billing, and finance systems and know how to resolve them.
• Analytical mindset with the ability to translate data into business narratives that support decision‑making.

• Experience with SaaS KPI reporting (e.g., net revenue retention, LTV, CAC payback).
• Hands‑on experience with Snowflake, dbt, and/or Power BI.
• Familiarity with data modeling best practices (dimensional modeling, slowly changing dimensions).