ERP/MRP Master Data Lead — Data Integrity & Analytics

Piper Companies; Audubon Gardens (PA); On-site; USD 90,000 - 100,000; Full time

Benefits offered by this job

Comprehensive Benefits

Job summary

Zachary Piper Solutions is seeking a Lead Master Data Analyst to ensure the integrity and accuracy of master data across manufacturing and supply chain operations. The role focuses on ERP/MRP data reliability to support planning and decision-making.

The ideal candidate has 8+ years of experience in master data or related analytics, plus hands-on ERP/MRP knowledge. Collaboration with cross-functional teams is essential for maintaining data standards and improving processes.

Qualifications

• 8+ years of experience in master data, supply chain analytics, manufacturing, data management, or related area.
• ERP/MRP experience required; strong understanding of how system data impacts planning.
• Experience managing or analyzing master data within manufacturing or supply chain environments.

Responsibilities

• Own and maintain master data integrity across ERP/MRP systems for manufacturing and planning.
• Analyze master data to identify discrepancies and gaps affecting production, inventory, procurement, and forecasting.
• Collaborate with Supply Chain, Manufacturing, Operations, Planning, Procurement and IT to maintain data standards and processes.
• Evaluate downstream impact of master data changes and recommend improvements to data quality.
• Serve as SME for master data and ERP/MRP processes to drive data-focused solutions.

Skills

Analytical skills

Problem solving

Communication

Cross-functional collaboration

Tools

ERP/MRP systems

Job description

Zachary Piper Solutions is seeking a Lead Master Data Analyst to ensure the integrity and accuracy of master data across manufacturing and supply chain operations. The role focuses on ERP/MRP data reliability to support planning and decision-making.

The ideal candidate has 8+ years of experience in master data or related analytics, plus hands-on ERP/MRP knowledge. Collaboration with cross-functional teams is essential for maintaining data standards and improving processes.