ERP Data Migration Analyst

Job Title: ERP Data Migration Analyst

Industry: Manufacturing

Location: Corning, NY

Shift: Monday to Friday, 8:00 AM to 5:00 PM

Top 3 Skills

• ERP data migration validation, including data profiling, cleansing, and reconciliation
• Procure-to-pay (Req to Pay) process and transactional data
• Dashboard, exception report, and reconciliation tool development

What You ll Do

• Validate that Req to Pay data transfers accurately during ERP deployments and go-lives
• Confirm data requirements, validation criteria, priorities, and status with the ERP transformation data team, business leads, and users
• Profile data to find anomalies, gaps, inconsistencies, and transfer risks
• Filter, cleanse, and reconcile data using reports and performance indicators
• Collect data from primary and secondary sources and maintain the databases and files that support validation
• Build data collection processes and validation methods that improve quality and consistency
• Mine and analyze large data sets with statistical tools to spot trends and patterns
• Build dashboards, visualizations, exception reports, and reconciliation tools
• Apply AI-enabled and automation approaches to speed up issue identification and pattern detection
• Turn findings into clear updates and recommendations for management and stakeholders

What We Need From You

• Bachelor s degree in IT, Science, or Business
• 5 years in data validation, data analysis, ERP data support, or transformation roles
• Hands-on experience supporting ERP deployments, data migration, or system implementations, including profiling, cleansing, and reconciliation
• Working understanding of Req to Pay (procure-to-pay) processes and data
• Experience building dashboards, reports, or validation tools, and the ability to work 100% onsite in Corning, NY

Preferred / Bonus

• SAP S/4HANA or a similar ERP platform
• Req to Pay data validation, migration, or deployment readiness experience
• Databricks or other AI, automation, or advanced analytics tools
• Enterprise data quality and statistical analysis methods
• Cross-functional global transformation programs