Senior Materials Planner - Logistics & Supply Chain

IAC International Automotive India Pvt. Ltd.; Santa Catarina; Presencial; MXN 220.000 - 360.000; Jornada completa

Descripción de la vacante

IAC Group is seeking a Materials & Logistics Coordinator to drive planning and supply chain activities in a fast-paced manufacturing environment. You will develop and monitor MRP processes, manage material requirements, and ensure timely delivery aligned with customer schedules.

The role requires experience in materials planning, automotive logistics, and collaboration across Production, Purchasing, Warehouse, Quality and Suppliers. SAP/ERP proficiency and strong data analysis are essential.

Formación

• 2–5 years of experience in materials planning and automotive logistics.
• Experience in automotive industry (Tier 1 or 2) preferred.
• Experience in plastic injection moulding or continuous manufacturing desirable.

Responsabilidades

• Develop and monitor MRP to ensure timely supply according to schedules.
• Analyse raw material requirements and manage stock levels to prevent stoppages and obsolescence.
• Coordinate with production, purchasing, warehouse, quality and suppliers to secure materials.
• Lead actions on supply risks, shortages or demand changes and participate in new project launches.

Conocimientos

MRP / ERP systems (SAP, QAD, Oracle)

Forecasting & demand planning

Inbound & outbound logistics

Inventory & warehouse control

Incoterms & transport

IATF 16949 supply chain requirements

Advanced Excel / data analysis

Conversational English

Descripción del empleo

IAC Group is seeking a Materials & Logistics Coordinator to drive planning and supply chain activities in a fast-paced manufacturing environment. You will develop and monitor MRP processes, manage material requirements, and ensure timely delivery aligned with customer schedules.

The role requires experience in materials planning, automotive logistics, and collaboration across Production, Purchasing, Warehouse, Quality and Suppliers. SAP/ERP proficiency and strong data analysis are essential.