Senior Finance Business Partner
Pubblicato il 19-08-2026 - Siemens Mobility in Milano
At Siemens, we enable sustainable progress through technology, connecting the real and digital worlds to improve how we live, work, and move.
We put our people first - creating a diverse, global environment where you can grow, take ownership, and make a real impact from day one.
Here, your ideas turn into innovative solutions that transform industries, infrastructure, mobility and everyday life.
Your next chapter starts here
Your role:
As a Senior Finance Business Partner, you will be a key part of the Siemens Finance Team of In Italy, contributing to the financial success of the Electrification and Automation Business Unit. Your day-to-day activities will include Financial Controlling, Business Partnering with the Segments and driving improvement initiatives.
Siemens Electrification and Automation (EA) Business Unit is a global leader in innovative solutions for efficient energy distribution and smart automation. Focused on sustainability and digitalization, we drive smarter, greener, and more connected systems — empowering industries, utilities, and infrastructure worldwide.
You’ll make an impact by:
- Being a team player, a strong communicator and a structured analytical mindset with a passion for digitalization
- Driving financial performance through data analysis and process improvements.
- Managing compliance and ensuring accurate financial metrics.
- Collaborating with teams to implement AI tools and automation, enabling smarter decisions and efficiencies.
- Analyzing monthly, quarterly, and annual financial results, ensuring compliance with corporate policies and governance standards.
- Monitoring key metrics, such as revenue, margins, operating expenses, and working capital, to support business objectives.
- Partnering with Proposal, Product and Execution Team to define start-of-the art financial processes
- Driving initiatives to improve inventory accuracy, working capital, and governance structures
- Optimizing Inventory Processes through data-driven insi