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.
What Success Looks Like
-
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 Real Challenge
-
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
What You Will Do
-
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
Required
-
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
Nice to Have
-
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)
