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Data Engineer/Analyst

Pubblicato il 12-08-2026 - Ion in Pisa

About ION

We are a Software Product Company with a global footprint in the FinTech sector. With more than 10,000 professionals across 40+ offices worldwide, we provide solutions combining trading and workflow automation, market data, and advanced business intelligence.

Our Graduate Development Program is a three‑year journey designed for recent graduates who look beyond the obvious, challenge existing processes, and are driven to automate and reinvent the way things work. The program is structured into four progressive phases, each with distinct learning objectives. Tasks evolve according to your abilities and interests, ensuring the experience is as individual as you are.

From day one, you join ION on a full‑time permanent contract, carry real accountability on live projects, and be paired with senior professionals who guide your development throughout the entire journey.

What you’ll do
- Interacting with business and process owners to understand data sources, reconstruct their semantics, and assess their value
- Performing exploratory data analysis, reverse engineering,



and building multidimensional BI models as a single source of truth
- Automating data extraction, cleaning, transformation, enrichment, and standardization to feed central Data Hubs
- Implementing automated reporting across multiple channels — Power BI dashboards, programmatic PowerPoint generation, and custom web UIs
- Managing and maintaining operational data pipelines end‑to‑end

What we’re looking for
- Master’s degree in a STEM discipline — obtained within the last year or currently in progress, with a strong academic record
- Solid command of Python and SQL for data analysis; familiarity with statistical concepts and time series analysis is a plus
- Strong communicator, collaborative by nature, and fluent in both English (B2+) and Italian
- Based in Italy or willing to relocate; non‑EU candidates must hold a valid EU work permit

Nice to have

Power BI, Databricks or Apache Spark, DBMS /

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