Data Governance Analyst

AWC, Inc.•Deer Park, TX

About The Position

As a Data Governance Analyst at AWC, you will play a critical role in establishing and maintaining the product data standards, taxonomy, governance controls, and processes that support the organization’s continued growth and digital transformation. You will help ensure our product and business data is accurate, consistent, well-structured, and trusted - creating a strong foundation for automation, analytics, reporting, and data-driven decision-making across the organization. Working collaboratively with teams across the business, you will help define data standards, improve data quality, identify opportunities for process improvement, and establish governance practices that enable our systems and people to operate more effectively. This is a unique opportunity to combine analytical thinking, technical curiosity, and cross-functional collaboration to make a meaningful impact within a growing leader in industrial automation and process technology.

Requirements

Data governance experience: Strong understanding of data ownership, data standards, taxonomy, attribute management, and governance controls that support consistent product data across systems
Analytics and problem-solving skills: Ability to analyze large data sets, identify trends, uncover root causes, and translate findings into practical recommendations for process and data quality improvement
AI knowledge and applied automation awareness: 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
Report-building ability: 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
DRP and business process knowledge: Familiarity with DRP concepts, item data flows, demand and supply planning impacts, and how accurate product data supports downstream operational decisions
Attention to detail and data discipline: Commitment to accuracy, consistency, documentation, and follow-through when reviewing data, maintaining standards, and enforcing governance rules
Cross-functional communication: 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

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