Product Data Analyst I — BOM/PLM Data Steward

iSupport Worldwide; Hinoba-an; On-site; PHP 300,000 - 520,000; Full time

Benefits offered by this job

Free lunch

Onsite gym

Upskilling academy

Modern office facilities

Employee amenities

Job summary

iSupport Worldwide is seeking a Product Data Analyst to oversee product data governance, BOM management, and lifecycle administration. You will ensure data quality across ERP and PLM, support ECOs, and manage supplier data for consumer goods projects.

Ideal candidates hold a Bachelor’s degree with 1–2 years in PLM environments and strong Excel skills, aiming to improve data accuracy and process efficiency.

Qualifications

• Bachelor’s degree in Business Administration, Supply Chain, Information Systems, Industrial Engineering, or related field.
• 1–2 years of experience in Product Data Management, BOM creation/maintenance, and PLM systems.
• Strong understanding of BOM structures, product lifecycle processes, and product master data management.
• Experience with ERP systems, preferably Oracle EBS.
• Advanced Microsoft Excel skills.
• Experience handling large datasets with emphasis on accuracy and validation.

Responsibilities

• Manage and validate product data across the lifecycle.
• Ensure data accuracy across ERP and PLM systems.
• Create and maintain SKUs, UPC/GTIN, and EAN codes.
• Handle BOM assignments in Oracle EBS and PLM.
• Maintain Colour Variant BOMs and Packaging BOMs.
• Execute ECOs and support engineering transitions.

Skills

Excel proficiency

Data validation

Detail oriented

Stakeholder management

English communication

Education

Bachelor’s degree

Tools

Oracle EBS

PLM systems

Job description

iSupport Worldwide is seeking a Product Data Analyst to oversee product data governance, BOM management, and lifecycle administration. You will ensure data quality across ERP and PLM, support ECOs, and manage supplier data for consumer goods projects.

Ideal candidates hold a Bachelor’s degree with 1–2 years in PLM environments and strong Excel skills, aiming to improve data accuracy and process efficiency.