About us
Traditional banking has never really given you control over your financial life. Satispay exists to change that: to empower people through finance.
That means making financial services easy and accessible for over 6.5M users. We started with payments, then benefits, investing, cards... and we’re not done. Not even close.
We follow the same logic every time: find a real problem, solve it properly, then look for the next one. The destination? To build the most loved financial platform in the world.
If you own outcomes rather than tasks, stay close to what users need, and refuse to wait for someone else to fix what's broken — you'll find people here who work exactly in the same way. And together, you'll build something worth being proud of.

What you'll be doing
As our Data Analyst - Analytics Engineering, you'll own driving our data strategy and enhancing decision-making by developing scalable data assets and AI-powered workflows within the Growth & Marketing (G&M;) B2C Analytics team.
Here's what that looks like in practice:




- Lead Design Data Architecture - Drive the development of the Data Mesh layer by designing robust data models and building pipelines that integrate into the company's federated data strategy, ensuring scalable and governed data ownership.
- Define AI Agentic Workflows - Design and implement AI-powered agentic workflows for data transformation and exploration, accelerating analytical capabilities and enabling self-service for key stakeholders.
- Build High-Impact Visualisation Tools - Define key metrics and develop dashboards and reports (using tools like Hex or Looker) that communicate analytical insights effectively.
- Drive Decision-Making Through Data - Analyse complex datasets to identify patterns impacting the consumer funnel (Acquisition, Engagement, Retention, Monetisation) and partner with Marketing Managers to maximise ROI.
- Partner with Key Stakeholders - Act as a strategic partner for Marketing, Finance, Operations, and Produ

📌 Data Analyst (Milano)
🏢 Satispay
📍 Milano