Financial Analyst
Pubblicato il 29-09-2026 - Magna International in Pavia
What we offer At Magna, you can expect an engaging and dynamic environment where you can help to develop industry-leading automotive technologies. We invest in our employees, providing them with the support and resources they need to succeed. As a member of our global team, you can expect exciting, varied responsibilities as well as a wide range of development prospects. Because we believe that your career path should be as unique as you are.
Group Summary The Mechatronics, Mirrors and Lighting group specializes in automotive technologies that are driving the future of mobility. Combining a deep systems knowledge to develop unique vehicle access experiences, intelligent vision systems and advanced automotive lighting technologies, MML's expertise light the path to innovation, safety and styling.
Job Responsibilities We are looking for a Financial Analyst who will assist in managing and consolidating financial performance across multiple entities within the group. This position emphasizes group-level controlling, reporting, and automation initiatives to ensure accurate, timely,
and efficient financial processes. The ideal candidate combines logical mindset and controlling with strong skills in process automation and digital finance transformation. The position in Italy is permanent, in Germany it is initially a two-year fixed-term contract with the option of conversion to a permanent position.
Key Responsibilities
- Group Controlling & Consolidation: Assist the preparation and consolidation of monthly, quarterly, and annual group financial results. Apply checks of compliance with group accounting policies. Analyze group performance, variances, and key financial indicators; provide actionable insights to senior management.
- Automation & Digital Transformation: Drive automation of group reporting and controlling processes using tools such as Power BI, RPA, Python, and ERP automation modules. Develop dashboards and automated workflows to improve data accuracy and reduc