JOB SUMMARY:

The SAP Data Clerk is responsible for accurately entering, maintaining, and managing inventory and logistics data within the SAP system. This role supports warehouse operations by ensuring accurate stock records, tracking inventory movements, and generating reports to optimize efficiency.

MINIMUM QUALIFICATIONS:

• High school diploma or equivalent (Associate’s or Bachelor’s degree in Logistics or related field preferred).
• 1-3 years of experience in SAP data entry, inventory control, or warehouse clerical roles.
• Experience in warehousing, logistics, or supply chain industry preferred.
• Previous experience in warehouse or logistics data entry, preferably using SAP (WM, MM, or IM modules).
• Strong understanding of warehouse processes, inventory management, and supply chain operations.
• Proficiency in SAP and Microsoft Office (Excel, Word, Outlook).
• Excellent attention to detail and data accuracy.
• Good organizational and time-management skills.
• Ability to work in a fast-paced warehouse environment.
• Strong communication and teamwork skills.

• Inventory Data Entry: Accurately input stock movements, receipts, shipments, and adjustments in the SAP system.
• Stock Reconciliation: Ensure SAP inventory records match physical stock levels by conducting regular audits and cycle counts.
• Warehouse Operations Support: Coordinate with warehouse staff to maintain accurate records of incoming and outgoing goods.
• Order Processing: Assist in processing warehouse orders, including picking, packing, and dispatching stock data in SAP.
• Report Generation: Generate and distribute stock reports, order tracking logs, and inventory analysis for management.
• Data Accuracy & Compliance: Ensure all warehouse data entries comply with company policies, safety regulations, and operational standards.
• Issue Resolution: Identify and resolve discrepancies in stock movements, purchase orders, and shipments within SAP.
• Communication: Work closely with warehouse teams, procurement, and logistics to ensure seamless data flow and operational efficiency.