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Data Analyst

Pubblicato il 07-09-2026 - Moneyfarm in Milano

We are a rapidly growing pan-European digital wealth manager, serving over 167,000 active investors with more than £5.5 billion invested on our platform. We began in Milan in 2011 with the purpose to help more people improve their financial well-being by making personal investing simple and accessible through technology. Fast forward to today, and we are recognised as one of the most innovative fintechs, headquartered in the heart of London.
Scopra esattamente quali competenze, esperienze e qualifiche sono necessarie per avere successo in questo ruolo prima di candidarsi.
With a team of 220+ people across 4 offices in Italy and the UK, we are proudly backed and funded by major partners including Poste Italiane, Cabot Square Capital, United Ventures, and Allianz.
About the role
Are you excited about making a real impact on the way Moneyfarm makes decisions? If you are an engineering‐minded data analyst ready to get hands‐on on a Data Platform supercharged with AI this role is for you.




You will join Moneyfarm's Data Team as a Data Analyst working closely with either product verticals (Trading, Wealth, Pension, Acquisition) or CEO office. You will act as the Data Enabler for your working group, turning raw data into trusted, well‐defined information that product managers, business stakeholders (including C-level) and engineers can act on autonomously.
With surface‐level output produced by AI, your job will be to orchestrate that work and be accountable for it: reviewing code, creating data models, writing tests, and curating the context our AI agents rely on. You will own the analytical narrative and KPIs of your area and safeguard the quality of its data.
Main Responsibilities
- Build a profound understanding of the business context you will be embedded into.
- Direct AI tools to build queries, dashboards and reports, and take full accountability for the output.
- Design, build and maintain analytics‐ready DBT data models, applying software‐engineering best practices

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