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Since 2004, we've had one clear goal: to make payments and money management effortless for every business in Europe. Today, more than 300,000 companies use Mollie to get paid, manage money and grow – with products designed to be simple, scalable, and dependable. With 950+ Mollies across 14+ locations, we care deeply about autonomy and craft. So we work in small teams, with real ownership, and we trust you to make the right decisions. We're building for the long term, so we provide the tools you need, processes you can rely on, and a balanced work environment to help you do work you're proud of. Customer support is one of the most direct touchpoints between Mollie and the businesses we serve. As an Analytics Engineer on the Support Optimization team in Lisbon, you'll make sure the people running that support function have the data, visibility, and insight they need to operate at their best. You'll help build and maintain the analytical infrastructure that keeps our support teams sharp, from defining the KPIs that measure what actually matters, to building the real-time reporting that helps teams act on what they see. You'll also play a meaningful role in two significant transitions: our platform migration from Zendesk to Open, and the rollout of AI-powered support agents. Your analysis will directly shape how those changes land while continuously providing insights that can drive improvement for operations. This is a role for someone who is comfortable working close to the operational detail, building things that get used every day, and asking the right questions before reaching for the data.
Job Responsibility
Dashboards in Omni that give support teams clear, reliable visibility into performance and operations
Data models in dbt that create a solid, maintainable foundation for support analytics
Real-time reporting via Plecto that surfaces operational insights when they're actually needed
KPI frameworks that define how support performance is measured and tracked across teams
Impact analyses on the introduction of AI customer support agents, helping the business understand what's working and what needs to change
Reports and presentations that translate data into clear recommendations for stakeholders
Requirements
+ years of experience in analytics engineering, data analytics, business intelligence, or equivalent demonstrable experience using data to help businesses.
Advanced SQL proficiency and a strong understanding of data modeling principles.
Proven experience building and scaling data models using dbt or an equivalent stack (e.g., SQL + Airflow).
Deep experience with at least one modern BI or data visualization tool (e.g. Looker, Tableau, etc.).
A track record of taking raw, complex data sources and modeling them into useful, clean, production-ready datasets.
The ability to translate business problems into data questions and clearly communicate findings to non-technical partners.