Context & Impact
As Lansweeper scales its SaaS business across new products and markets, revenue analytics has become a critical function for steering executive and board-level decisions. This role exists to bring structure, trust, and clarity to how Lansweeper measures and understands its revenue.
You will be the dedicated Revenue Analytics Engineer within a 10-person Data & Analytics team — the first hire focused entirely on revenue — reporting directly to the Data Platform Manager. Your work will directly shape how C-level leaders and the board understand growth, and how sales and finance teams plan and act.
In the near term, your goals are to establish a single source of truth for revenue KPIs, build board-ready reporting, and deliver forecasting models that drive go-to-market decisions.
Challenge
The main challenges you'll face are:
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Speed vs. complexity: The sales organization moves fast and needs reliable revenue facts quickly — but revenue data is sourced from multiple systems (CRM, billing, ERP) with historic complexity from acquisitions and system migrations, and data quality that varies over time.
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Keeping up with a changing business:** As Lansweeper's product and market evolve, sales and marketing allocation must follow. You'll need to continuously adapt revenue models to reflect new business processes and priorities.
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Being the first and only:** You are the sole analytics engineer focused on revenue. You'll need to build foundations from scratch, establish trust in the numbers, and earn your seat at the table with finance and executive stakeholders — all at the same time.
Key Responsibilities
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Build, maintain, and improve revenue data models** that power executive-level reporting and board-ready metrics across ARR, MRR, churn, expansion, contraction, and renewal cycles
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Reconcile revenue data across systems of record** — CRM, billing, and ERP — and establish a single, trusted source of truth for financial KPIs
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Design and deliver dashboards and reports** that translate complex revenue data into clear, actionable insights for sales, finance, and leadership
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Partner with sales operations and finance** to understand evolving business processes and reflect them accurately in revenue analytics models
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Develop and maintain forecasting models** for key revenue metrics to support go-to-market planning and strategic decision-making
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Investigate and explain trends, anomalies, and shifts** in revenue data, linking them back to underlying sales and finance drivers
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Proactively improve data quality and integrity** across revenue-related data pipelines to ensure consistent, reliable reporting
Key Requirements
Hard Skills
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Financial metrics reporting — solid understanding of how revenue, bookings, churn, ARR, MRR, expansion, contraction, and renewal KPIs are defined and measured in a SaaS context
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Strong SQL skills — ability to write, optimize, and debug complex queries against large datasets
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Systems reconciliation — hands-on experience resolving data mismatches between CRM, billing, and finance systems to produce a reliable single source of truth
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Data modelling — familiarity with best practices such as dimensional modelling and slowly changing dimensions; experience with Snowflake and dbt is a strong plus
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Dashboard and reporting delivery— experience building clear, business-facing reports; experience with **Power BI** is a strong plus
Soft Skills
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Analytical storytelling — you translate data into business narratives that support decisions, not just numbers on a screen
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Stakeholder collaboration— you work confidently with finance, sales ops, and executive audiences, adapting your communication to each
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Ownership mindset — you take initiative, work independently, and drive outcomes without waiting to be directed
AI-Specific Skills
Lansweeper is an AI-native company. In this role, AI fluency is a hard requirement — not a nice-to-have.
You are expected to use AI tooling as a standard part of your day-to-day workflow: this includes AI-assisted SQL generation and debugging, using AI to accelerate data modelling and anomaly investigation, and leveraging AI features within your analytics stack (such as Snowflake Cortex or dbt-integrated tooling). You should be comfortable prompting AI tools effectively, evaluating their outputs critically, and integrating AI into repeatable workflows — from data pipeline development to generating draft narrative summaries for executive reporting. General AI fluency across platforms such as ChatGPT or Copilot is expected.
Team Info
You'll join the Insights & Intelligence team, part of the broader Data & Analytics function at Lansweeper. The team has 10 people and is led by the **Data Platform Manager**, who you will report to directly. You will work closely with sales operations, finance, and data engineers across the organization.
As the **only analytics engineer focused on revenue**, you will own this domain end-to-end — a rare opportunity to define how a growing SaaS company understands and steers its revenue.
The team is based across Ghent, Belgium and Alicante, Spain, with a hybrid working model at both locations.
Our Offer
Salary:
See Pay Transparency section below.
Benefits — Belgium:
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Meal vouchers
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Eco vouchers
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Hospitalisation insurance
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Group insurance
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Company car or mobility budget
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Phone plan
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Internet allowance
Benefits — Spain:
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Health insurance
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Meal allowance
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Flexible remuneration plan
What else you get:
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A high-impact, high-autonomy role at the intersection of data, finance, and go-to-market strategy
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Hybrid working from either **Ghent, Belgium or Alicante, Spain** — flexibility built in by design
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A pragmatic, collaborative data team that values ownership and real-world impact over process for process's sake
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The opportunity to **build the revenue analytics function from the ground up** in a scaling SaaS company
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A front-row seat to C-level and board decision-making, with your work directly influencing strategic direction
About Lansweeper
Lansweeper is the AI Cyber Asset Intelligence platform helping IT and Security teams gain full visibility, reduce cyber risk, and scale automation with confidence.
In today's complex IT, OT, cloud, and IoT environments, fragmented asset data slows decisions and increases risk. We transform raw asset data into a continuously validated, trusted source of truth — so teams can move faster and act with certainty.
With Lansweeper, organizations can:
See – Truly complete visibility across hybrid environments
Know– Enriched asset intelligence with lifecycle and risk context
Act – Automate workflows, coordinate remediation, and enforce policy at scale
From universal asset discovery to AI-powered intelligence, we provide the shared foundation modern IT Operations, Cybersecurity, and Digital Transformation teams rely on.
Our culture — built on four core values:
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One Team – United across boundaries
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We Care – Customers and people at the centre
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We Grow – Learning, sharing, improving
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We Deliver – Focusing on what truly matters
Pay Transparency
At Lansweeper, every role is assigned to a level defined by three things: the expertise it requires, the complexity it involves, and the scope of impact it carries.
Each level maps to a salary band based on salary benchmarks from the Software/SaaS industry of your country, so your pay reflects what the market pays for comparable roles.
The gross salary range for this role is €107,000 – €174,000 (EUR) (Belgium) or €75,000 – €123,000 (EUR) (Spain) (based on full-time employment).
Where you land within that range depends on the expertise you bring, the complexity you have navigated, the scope of impact you have owned, and your track record of delivering results in comparable roles — the same criteria applied consistently to every candidate.
We welcome applicants of all backgrounds, regardless of gender, religion, ethnic origin, age, sexual orientation, or disability.
How AI Is Used During the Hiring Process
We use AI to support and not replace during the hiring process. HR decisions are made by our talent acquisition team. You can request more info at any time via [email protected]
Diversity Statement
It is Lansweeper's policy to provide equal employment opportunity to all applicants and employees.
Lansweeper disapproves of, and will not tolerate, unlawful discrimination against any applicant or employee because of race, color, national origin or ancestry, gender (including pregnancy, childbirth, or related medical conditions), gender identity, age, religion, disability, family care status, veteran status, marital status, sexual orientation, or any other basis protected by local, state, or federal laws.
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Key Requirements
Hard Skills
-
Financial metrics reporting — solid understanding of how revenue, bookings, churn, ARR, MRR, expansion, contraction, and renewal KPIs are defined and measured in a SaaS context
-
Strong SQL skills — ability to write, optimize, and debug complex queries against large datasets
-
Systems reconciliation — hands-on experience resolving data mismatches between CRM, billing, and finance systems to produce a reliable single source of truth
-
Data modelling — familiarity with best practices such as dimensional modelling and slowly changing dimensions; experience with Snowflake and dbt is a strong plus
-
Dashboard and reporting delivery— experience building clear, business-facing reports; experience with **Power BI** is a strong plus
Soft Skills
-
Analytical storytelling — you translate data into business narratives that support decisions, not just numbers on a screen
-
Stakeholder collaboration— you work confidently with finance, sales ops, and executive audiences, adapting your communication to each
-
Ownership mindset — you take initiative, work independently, and drive outcomes without waiting to be directed
AI-Specific Skills
Lansweeper is an AI-native company. In this role, AI fluency is a hard requirement — not a nice-to-have.
You are expected to use AI tooling as a standard part of your day-to-day workflow: this includes AI-assisted SQL generation and debugging, using AI to accelerate data modelling and anomaly investigation, and leveraging AI features within your analytics stack (such as Snowflake Cortex or dbt-integrated tooling). You should be comfortable prompting AI tools effectively, evaluating their outputs critically, and integrating AI into repeatable workflows — from data pipeline development to generating draft narrative summaries for executive reporting. General AI fluency across platforms such as ChatGPT or Copilot is expected.
