Summary
AWC, Inc. is an employee-owned provider of industrial automation and process technology solutions. The Data Governance Analyst will establish and maintain product data standards, taxonomies, governance controls, and quality processes to ensure accurate, consistent, and trusted data. The role supports automation, analytics, reporting, integrated systems, and data-driven operations through cross-functional collaboration.
Responsibilities
- Define, maintain, and continuously improve product taxonomy, classification hierarchies, and naming standards
- Establish required attribute frameworks that ensure all items are consistently defined and usable across systems
- Design and manage controlled value lists that enable standardized, reliable data entry and reporting
- Govern attribute definitions to ensure consistency across product lines, sites, and functional use cases
- Partner with stakeholders to evolve taxonomy structures as product complexity and automation needs increase
- Design and administer duplicate-prevention rules to eliminate redundant item creation and maintain a single source of truth
- Implement validation logic and entry controls within ERP and upstream systems to enforce data completeness and accuracy
- Monitor data health using exception reporting, identifying trends in incomplete, inconsistent, or invalid data
- Drive corrective actions for systemic data quality issues, ensuring root causes are addressed—not just symptoms
- Maintain governance over item creation workflows to ensure adherence to standards and rules
- Develop and maintain data governance scorecards including completeness, accuracy, and compliance metrics
- Establish routine audit processes to validate adherence to taxonomy, attribute standards, and governance policies
- Provide visibility to leadership on data health, risks, and improvement opportunities
- Track and trend data quality performance over time, linking improvements to operational outcomes
- Support audit readiness for internal and external requirements where product data integrity is required
- Ensure product data structures support safe and scalable automation in CPQ, order management, and supply chain workflows
- Enable consistent data consumption across integrated systems including ERP, reporting tools, and external interfaces
- Collaborate with IT and business stakeholders to align governance standards with system capabilities and integrations
- Reduce manual intervention by strengthening upstream data quality and governance discipline
- Support expansion of automated workflows by ensuring data inputs are stable, complete, and reliable
Skills
- Strong understanding of data ownership, data standards, taxonomy, attribute management, and governance controls that support consistent product data across systems
- Ability to analyze large data sets, identify trends, uncover root causes, and translate findings into practical recommendations for process and data quality improvement
- Working knowledge of how AI, automation, and machine learning concepts can be used to improve data quality, detect patterns, reduce manual effort, and support smarter reporting and decision-making
- Experience creating clear, reliable reports, dashboards, scorecards, and exception views that communicate data health, compliance, risks, and improvement opportunities to both technical and business audiences
- Familiarity with DRP concepts, item data flows, demand and supply planning impacts, and how accurate product data supports downstream operational decisions
- Commitment to accuracy, consistency, documentation, and follow-through when reviewing data, maintaining standards, and enforcing governance rules
- Ability to partner with stakeholders across operations, IT, supply chain, product teams, and leadership to explain requirements, resolve data issues, and drive adoption of governance practices
Qualifications
Must Haves
- Strong understanding of data ownership, data standards, taxonomy, attribute management, and governance controls that support consistent product data across systems
- Ability to analyze large data sets, identify trends, uncover root causes, and translate findings into practical recommendations for process and data quality improvement
- Working knowledge of how AI, automation, and machine learning concepts can be used to improve data quality, detect patterns, reduce manual effort, and support smarter reporting and decision-making
- Experience creating clear, reliable reports, dashboards, scorecards, and exception views that communicate data health, compliance, risks, and improvement opportunities to both technical and business audiences
- Familiarity with DRP concepts, item data flows, demand and supply planning impacts, and how accurate product data supports downstream operational decisions
- Commitment to accuracy, consistency, documentation, and follow-through when reviewing data, maintaining standards, and enforcing governance rules
- Ability to partner with stakeholders across operations, IT, supply chain, product teams, and leadership to explain requirements, resolve data issues, and drive adoption of governance practices
Benefits
- Employee Stock Ownership Plan (ESOP)
- 401(K) Match
- Medical, Dental and Vision Insurance Package
- Employer Paid Life Insurance
- Paid Time Off and Holiday Pay
- Career Development Opportunities