Data Engineer Python,aws Remote
Pubblicato il 06-09-2026 - Prada Group in Italia
Founded in 1913 in Italy, the Prada Group was built on a tradition of excellence and with a vision of innovation. The Group, a world leader in the luxury sector, operates in more than 45 countries with the PRADA, Miu Miu, Versace, Church's, Car Shoe and Luna Rossa brands, and has employees of over 100 nationalities. Job Purpose
We are looking for a Data Engineer to join our global Cloud Data Platform team, based in Milan. The ideal candidate will play a key role in managing data operations, with main activities ranging from analysis, modeling and development, with a strong focus on sales, customer, and marketing data.
Responsibilities
Gain a deep understanding of business and technical needs to support model evolution and drive digital transformation. A particular focus will be on customer intelligence data and sales KPIs.
Design, maintain, and enhance key datasets to ensure they are high-quality, certified, and easily accessible/integrable by enterprise users, components, and systems.
Analyze and develop data operations and pipelines in line with enterprise guidelines and best practices (e.g., data quality processes, governance, and deep catalog/glossary curation).
Work collaboratively with business stakeholders and end users to build scalable and agile solutions.
Develop, deploy, and manage highly efficient and automated data pipelines using cloud-based technologies and platform capabilities (e.g., Azure, Databricks, Unity Catalog, Git based CI/CD).
Continuously adapt to evolving requirements by maintaining and improving existing data pipelines, integrating new features and change requests using an agile approach.
Knowledge And Skills
Bachelor or Master's degree in Software Engineering, Computer Science, Mathematics or related STEM discipline
3+ years experience in intensive data ops. in the context of Big Data and cloud infrastructures / platforms
Strong experience in analytics in the context of retail industry, with a particular focus on modeling and leveraging