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. 

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)