About us
Satispay began by rethinking the simple act of a payment to remove the friction from our daily routines. But we didn’t stop there. Today, we are building a complete financial platform designed to empower people and concretely improve their lives. By giving our 6 million users a clear, open path to pay, save, and invest, we are evolving into the definitive destination for every financial need.
What you'll be doing
As our Data Analyst – Analytics Engineering, you’ll be the person who drives our data strategy and enhances decision‑making by developing scalable data assets and AI‑powered workflows. You will join the Growth & Marketing (G&M;) B2C Analytics team, which sits at the heart of our department with the mission to put intelligence first in every decision.
- 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 Product, bridging the gap between technical data and business goals.
- Drive Testing Initiatives – Own the end‑to‑end testing pipeline, from opportunity identification to experiment design and recommendation delivery.

Who we're looking for
We need a problem‑solver who loves

📌 Data Analyst (Milano)
🏢 Satispay
📍 Milano