Regal Rexnord
Product Data Steward & Data Analyst
Regal Rexnord, Milwaukee, Wisconsin, United States, 53202
Product Data Steward & Data Analyst
The Product Data Steward & Data Analyst is a critical role responsible for ensuring the accuracy, integrity, and completeness of product master data across the manufacturing value chain. Operating at the intersection of engineering, supply chain, and commercial operations, this role ensures product data in ERP, PIM, and MDM systems is governed, standardized, and analytics-ready. The steward collaborates with IT and business stakeholders to maintain high-quality data supporting manufacturing processes, product lifecycle management (PLM), and digital transformation initiatives. Essential Duties and Responsibilities: Product Master Data Governance & Lifecycle Management:
Define and enforce data standards for product hierarchies, material types, units of measure, commodity codes, and engineering attributes.
Oversee end-to-end product lifecycle datafrom item creation and engineering release through phase-outensuring alignment with engineering change control processes.
Ensure data synchronization between ERP (e.g., SAP ECC, Oracle EBS), MDM platforms (e.g., Informatica), and PIM systems for consistent global product definitions. Data Quality Monitoring & Reporting:
Develop and maintain dashboards and scorecards for product data quality metrics such as completeness, accuracy, uniqueness, and timeliness.
Monitor data anomalies related to duplicate parts, incorrect UoM conversions, and invalid BOM relationships; work with business owners to resolve root causes.
Coordinate with business and IT teams to support periodic data cleansing and enrichment projects. Integration Across Engineering & Operational Systems:
Support integration of product data between PLM systems (e.g., Teamcenter, Windchill), ERP, and MDM to ensure traceability of product attributes and compliance with internal standards.
Document source-to-target mappings and transformation logic between engineering, manufacturing, and commercial datasets.
Ensure readiness of product data for manufacturing execution systems (MES), sales configurators, and digital twin or IoT platforms. Technical Enablement & Data Stack Collaboration:
Work with data engineers and architects to model and transform product datasets in Snowflake or other cloud platforms for reporting and analytics use cases.
Define technical specifications for data ingestion pipelines (e.g., Fivetran, Informatica), transformation logic (dbt), and API payloads for consumption by internal systems.
Partner with BI teams to deliver insights on product mix, usage patterns, and component rationalization using tools like PowerBI and Tableau. Stakeholder Collaboration & Continuous Improvement:
Act as the SME for product data across manufacturing operations, sourcing, and engineering teams.
Lead workshops with plant engineers, product managers, and supply chain teams to validate product attributes, packaging data, and BOM configurations.
Champion automation, standardization, and reuse of product data elements to drive efficiency and cost reduction across the enterprise. Critical Competencies:
Detail-oriented with strong data quality mindset and problem-solving abilities.
Effective communicator across technical and business teamscapable of translating product data requirements into actionable deliverables.
Ability to manage data projects with multiple stakeholders across engineering, procurement, and operations. Education and Experience Requirements:
Bachelor's degree in Engineering, Industrial Technology, Supply Chain, or Information Systems.
5+ years of experience in product data stewardship, data analysis, or master data management within a manufacturing environment.
Strong working knowledge of ERP systems (SAP ECC, Oracle EBS) with hands-on experience in material master, BOMs, routings, and classification views.
Proficient in SQL and Excel; experience with data visualization tools such as PowerBI or Tableau. Familiarity with MDM tools (e.g., Informatica MDM), PIM solutions, and product lifecycle systems (e.g., PLM).
Understanding of integration technologies, including REST/SOAP APIs, JSON payloads, and ETL tools (e.g., Informatica, Fivetran, dbt).
Experience in documenting data flows, DFDs, and source-to-target mappings for engineering and commercial systems. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is frequently required to sit, talk and/or hear, and/or use hands to finger, handle, or touch objects, tools, or controls. The employee is occasionally required to stand, and/or walk. The employee must occasionally lift and/or move up to 50 pounds while moving files or small packages. Specific vision abilities required by this job include close vision and the ability to adjust focus. The mental and physical requirements described here are representative of those that must be met by an individual to successfully perform the essential functions of this position.
Work Environment:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Work is performed in an office and production environment. The noise level in the work environment is usually moderate. Must comply and adhere to all safety requirements including PPE specified by location. The work environment characteristics described here are representative of those individual encounters while performing the essential functions of this position.
The Product Data Steward & Data Analyst is a critical role responsible for ensuring the accuracy, integrity, and completeness of product master data across the manufacturing value chain. Operating at the intersection of engineering, supply chain, and commercial operations, this role ensures product data in ERP, PIM, and MDM systems is governed, standardized, and analytics-ready. The steward collaborates with IT and business stakeholders to maintain high-quality data supporting manufacturing processes, product lifecycle management (PLM), and digital transformation initiatives. Essential Duties and Responsibilities: Product Master Data Governance & Lifecycle Management:
Define and enforce data standards for product hierarchies, material types, units of measure, commodity codes, and engineering attributes.
Oversee end-to-end product lifecycle datafrom item creation and engineering release through phase-outensuring alignment with engineering change control processes.
Ensure data synchronization between ERP (e.g., SAP ECC, Oracle EBS), MDM platforms (e.g., Informatica), and PIM systems for consistent global product definitions. Data Quality Monitoring & Reporting:
Develop and maintain dashboards and scorecards for product data quality metrics such as completeness, accuracy, uniqueness, and timeliness.
Monitor data anomalies related to duplicate parts, incorrect UoM conversions, and invalid BOM relationships; work with business owners to resolve root causes.
Coordinate with business and IT teams to support periodic data cleansing and enrichment projects. Integration Across Engineering & Operational Systems:
Support integration of product data between PLM systems (e.g., Teamcenter, Windchill), ERP, and MDM to ensure traceability of product attributes and compliance with internal standards.
Document source-to-target mappings and transformation logic between engineering, manufacturing, and commercial datasets.
Ensure readiness of product data for manufacturing execution systems (MES), sales configurators, and digital twin or IoT platforms. Technical Enablement & Data Stack Collaboration:
Work with data engineers and architects to model and transform product datasets in Snowflake or other cloud platforms for reporting and analytics use cases.
Define technical specifications for data ingestion pipelines (e.g., Fivetran, Informatica), transformation logic (dbt), and API payloads for consumption by internal systems.
Partner with BI teams to deliver insights on product mix, usage patterns, and component rationalization using tools like PowerBI and Tableau. Stakeholder Collaboration & Continuous Improvement:
Act as the SME for product data across manufacturing operations, sourcing, and engineering teams.
Lead workshops with plant engineers, product managers, and supply chain teams to validate product attributes, packaging data, and BOM configurations.
Champion automation, standardization, and reuse of product data elements to drive efficiency and cost reduction across the enterprise. Critical Competencies:
Detail-oriented with strong data quality mindset and problem-solving abilities.
Effective communicator across technical and business teamscapable of translating product data requirements into actionable deliverables.
Ability to manage data projects with multiple stakeholders across engineering, procurement, and operations. Education and Experience Requirements:
Bachelor's degree in Engineering, Industrial Technology, Supply Chain, or Information Systems.
5+ years of experience in product data stewardship, data analysis, or master data management within a manufacturing environment.
Strong working knowledge of ERP systems (SAP ECC, Oracle EBS) with hands-on experience in material master, BOMs, routings, and classification views.
Proficient in SQL and Excel; experience with data visualization tools such as PowerBI or Tableau. Familiarity with MDM tools (e.g., Informatica MDM), PIM solutions, and product lifecycle systems (e.g., PLM).
Understanding of integration technologies, including REST/SOAP APIs, JSON payloads, and ETL tools (e.g., Informatica, Fivetran, dbt).
Experience in documenting data flows, DFDs, and source-to-target mappings for engineering and commercial systems. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Physical Demands:
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is frequently required to sit, talk and/or hear, and/or use hands to finger, handle, or touch objects, tools, or controls. The employee is occasionally required to stand, and/or walk. The employee must occasionally lift and/or move up to 50 pounds while moving files or small packages. Specific vision abilities required by this job include close vision and the ability to adjust focus. The mental and physical requirements described here are representative of those that must be met by an individual to successfully perform the essential functions of this position.
Work Environment:
The work environment characteristics described here are representative of those an employee encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. Work is performed in an office and production environment. The noise level in the work environment is usually moderate. Must comply and adhere to all safety requirements including PPE specified by location. The work environment characteristics described here are representative of those individual encounters while performing the essential functions of this position.