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# ERP Project - BOM Data Special

- **Company:** CFS, Inc.
- **Location:** Elkhart, IN, United States
- **Salary:** $79,500.0 - $85,000.0
- **Contract:** Permanent contract
- **Skills:** Big Data, Data Validation, Data Cleansing, Excel Pivot Tables, Lookup Table, Pattern Recognition, Pivot Tables, SAP Project Management, Powerquery, Data Management
- **Published:** May 21, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=36a6a627f614af66

## About the Role

Do you have experience in VLOOKUP function?, * Strong understanding of Bill of Materials (BOM) and data management processes.

 * Proficiency in Power Query, Excel pivot tables, and VLOOKUP/XLOOKUP functions.
 * Ability to recognize patterns and normalize large datasets.
 * Experience working with large datasets (500K+ rows) and ensuring data accuracy.
 * Familiarity with ERP systems and the ability to understand how legacy data impacts new systems.
 * Willingness to learn Power Query (training provided if basic knowledge exists).
 * Strong analytical and problem-solving skills.

## Description

About the Company and Opportunity of ERP Project - BOM Data Specialist:

 * Our client is a dynamic organization undergoing a critical ERP project with a focus on data management and cleansing.
 * They value precision, analytical thinking, and a commitment to continuous improvement.
 * This role offers the opportunity to work with large datasets and play a pivotal role in ensuring data accuracy and system efficiency., The ERP Project - BOM Data Specialist will be responsible for managing and cleansing large datasets, primarily focusing on Bill of Materials (BOM) updates. This role requires a keen eye for detail, strong analytical skills, and the ability to work with vast amounts of data - approximately 500,000 to 700,000 rows. Key responsibilities include:
*
Performing data management, data cleansing, and data validation.

 * Utilizing Power Query, pivot tables, and merge fields to normalize data and ensure accuracy.
 * Conducting VLOOKUP and XLOOKUP functions to compare datasets against a "data truth."
 * Identifying patterns within the data and implementing corrections as needed.
 * Comparing old system data to the new ERP system to ensure consistency and integrity.
 * Understanding the functional impact of legacy system data on subsets of the new system.
 * Collaborating with the team to address inconsistencies and improve data quality.


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