Data Engineer | International Project | Ispra, Italy
Pubblicato il 10-09-2026 - Ayesa Digital in Ispra
At Ayesa Digital we grow with you Every professional in our company is vital to us. Thanks to their talent, we continue to expand; today, we are a global team of over 11,000 people working toward a common goal.
Ayesa Digital is currently participating in high-impact European Union projects designed to address major European challenges and drive science and innovation. These are strategic technological projects based on collaborative initiatives that stand out for their international focus and a strong commitment to socially-oriented results.
We are looking for a Data Engineer to join an international project supporting a European Commission institution based in Ispra, Italy. The selected professional will contribute to the development, maintenance and operation of advanced data-driven solutions focused on environmental analysis, scientific modelling and policy support activities. Working within a multicultural and highly collaborative environment, you will help manage complex datasets, optimise data workflows, and support innovative initiatives involving analytics, machine learning,
and environmental impact assessment. Leap — we are waiting for you
What You Will Do (Responsibilities):
Design, develop, and maintain data pipelines integrating data from multiple internal and external sources.
Ensure data quality, integrity, governance, security, and accessibility throughout the entire data lifecycle.
Develop and optimise relational and non-relational databases, including SQL performance tuning and database management activities.
Process, validate, and manage environmental and scientific datasets using Python, R, and SQL.
Support the maintenance, enhancement, and operation of data-intensive modelling and analytical tools.
Retrieve, organise and prepare datasets required for large-scale analytical and modelling activities.
Execute data workflows, model runs, and data processing activities, producing structured outputs and analytical datasets.
Implement metadata managemen