Imerys is the world’s leading supplier of mineral-based specialty solutions for the industry with €3.4 billion in revenue and 12,300 employees in 40 countries in 2025. The Group offers high value-added and functional solutions to a wide range of industries and quick-growing markets such as solutions for the energy transition and sustainable construction, as well as natural solutions for consumer goods. Imerys draws on its understanding of applications, technological knowledge, and expertise in material science to deliver solutions which contribute essential properties to customers’ products and their performance. As part of its commitment to responsible development, Imerys promotes environmentally friendly products and processes in addition to supporting its customers in their decarbonization efforts.
Imerys is listed on Euronext Paris (France) with the ticker symbol NK.PA.
The Position
Purchasing Senior Data Analyst
Job Summary
JOB PURPOSE
This position is part of the Purchasing Process and Tools team in India
The Purchasing Data Analyst is responsible for all the master data related to the purchasing tools, working in collaboration with the Purchasing Master Data Administrator and other internal stakeholders for ongoing deployment and support of the Ivalua tool across the Imerys group.
He/ She will be part of a Purchasing process & tools team in India and is accountable for the following activities:
- Map all master data related to global purchasing
- Work on master data mapping between SAP S4 Hana (Opera) and Ivalua
- Work on mapping spend data from different ERPs with Ivalua.
- Work on a process improvement of data transfer between systems
The Purchasing Process & Tools team consists of 12 people in India (6), Greece (3), France (2), and Mexico (1).
KEY TASKS AND RESPONSIBILITIES
AI & Data Strategy
- Act as the primary Subject Matter Expert (SME) for all matters related to procurement data, system applications, and AI integration.
- Drive the AI w
📌 Purchasing Senior Data Analyst (Hyderabad)
🏢 Imerys
📍 Hyderabad
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