Analytics Engineer
Pubblicato il 17-08-2026 - Banche e finanza in Milano
Analytics Engineer II - Revenue Operations
The role: Location: Amsterdam or Milan
Remote/Hybrid: Hybrid
Your impact
Revenue Operations at Mollie serves around 200 internal stakeholders across sales, customer success, marketing, and partnerships. The analytics work done here feeds directly into how commercial teams make decisions, assign leads, and manage performance. When the data is right, the whole commercial engine runs better.
This role sits inside the GTM Enablement team, a small group focused on making Mollie's go‐to‐market motion faster and smarter. You will be the analytics engineering support for the team's projects. At the same time you will own reporting of our GTM domains, such as Merchant Sales and CSM & Customer Growth. That means the work you produce is immediately visible and measurable within the business.
The domain is actively growing and maturing. RevOps has recently adopted a full domain model and is being rebuilt as a proper product and engineering function. There is real space here to shape how analytics is delivered to commercial stakeholders,
not just execute on requests. Over time, the expectation is that the team shifts from reactive to proactive, and this role is central to making that happen.
What you'll ship
Own and maintain core dashboards for GTM domains, including CSM and Merchant Sales, serving as the source of truth for commercial stakeholders
Own and maintain HubSpot data models
Define success metrics, set up data tracking and reporting for GTM Enablement team projects
Reduce dashboard sprawl by establishing centralised, standardised reporting in Omni
Deliver ad‐hoc analysis and impact scoping to support decision‐making
What you'll bring
Strong SQL skills and hands‐on experience building dashboards and reports in BI tools such as Looker, Tableau, or similar
Solid data visualisation skills with the ability to translate complex data into clear, actionable outputs for commercial audiences
A working understanding of data modelling con