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As an Analytics Engineer in our Payments domain, you'll be the person who turns complex payment flows into clear, reliable data products that teams across Mollie can actually use. From monitoring critical payment metrics to tracking how payment methods perform, your work will directly shape how we understand and improve our products. You'll sit within a team of 2 Analytics Engineers and an AE Engineering Manager, embedded in a Cards team of around 15 people including PMs and product engineers. That means you'll work closely with the people building the product, not just reporting on it. You'll help translate business needs into data solutions, influence product strategy with evidence, and build the kind of self-serve tooling that frees teams to move faster and make smarter decisions. Over time, this role grows with you. As you build foundational data models and reporting, you'll take on increasing ownership of analytics within the payments domain moving from building the infrastructure to driving optimisation of key metrics like conversion and auth rates. The goal is to reduce ad-hoc dependency and create more time for the work that really moves the needle.
Job Responsibility:
Data modeling & architecture: Build and maintain robust, performant, and user-friendly data models that can power dashboarding to monitor critical payment metrics and track payment method performance for the Payments domain.
Collaborate with product and engineering: Work closely with product managers and engineers to embed data into the core of payments products. You’ll help translate complex payment flows into actionable insights, driving adoption of data products across teams.
Commercial insights: Partner with stakeholders to define and track key revenue and performance drivers, and use data to drive improvements in features and product adoption, customer engagement and product performance.
Data quality: Ensure high trust in payments data by implementing data quality validation checks, testing frameworks, and proactive monitoring.
Data culture & enablement: Contribute to a culture of technical rigour and data literacy. You will help mentor team members on analytics best practices and ensure knowledge is well-documented and accessible.
Requirements:
Strong analytics & modeling: You have a proven ability to build reliable and scalable data models using SQL and data principles. Hands-on experience with a modern data stack (e.g. dbt, Snowflake, BigQuery) is essential.
Deep commercial analysis: You don't just build tables, you ask 'Why?'. You have strong experience in product or commercial analytics, using data to answer ambiguous questions around customer behaviour, performance drivers, and growth opportunities.
Impactful communication: You excel at translating analysis into clear, actionable narratives for stakeholders. You confidently present your findings and influence decisions across a range of audiences.
Nice to have:
Prior experience working within Payments or Fintech industry
Hand-on experience analyzing and optimizing complex funnels, with a strong understanding of conversion drivers and drop-off.