Data Analyst, Global Supply Chain

As a global leader in precision measurement sensing technologies, VPG addresses an expanding array of applications in which accuracy, reliability, and repeatability make the difference. Whether in the design and safety of new generations of cars, trucks, and planes or optimizing advanced medical equipment and consumer products, VPG's deep engineering expertise makes the world safer, smarter, and more productive.       

We are seeking a highly motivated Data Analyst to join our Global Supply Chain team on a full-time basis:

Position Summary

We are looking for a highly analytical and business-oriented Data Analyst to support our Global Supply Chain organization. The role is responsible for transforming data into actionable insights, improving decision-making, ensuring data integrity, and driving automation and reporting across Procurement, Planning, Inventory, Manufacturing, and Logistics functions.

Key Responsibilities

• Analyze data from multiple systems and sources to identify trends, risks, and improvement opportunities.
• Develop and maintain dashboards, KPIs, and management reports.
• Perform data validation, reconciliation, and quality checks to ensure accuracy and consistency.
• Create automated reports, workflows, and data solutions that reduce manual effort.
• Partner with global stakeholders to translate business needs into analytical insights and reporting tools.

Key Competencies

• Strong business acumen and ability to connect data with business outcomes.
• Excellent analytical and problem-solving skills.
• High attention to detail and data accuracy.
• Effective communication and stakeholder management in a global environment.

Qualifications

• 5+ years of experience in Data Analytics, Business Intelligence, or Supply Chain Analytics.
• Experience working in a global, multi-site environment.
• Strong knowledge of Supply Chain processes, including Planning, Procurement, Inventory, and Logistics.
• Advanced SQL skills and experience with Power BI or similar visualization tools.
• Experience with data automation, data validation, and dashboard development.
• Knowledge of ERP systems (QAD, SAP, Oracle, or similar).
• Experience with Python, Power Query, or other analytics tools is an advantage.