Data Governance and Quality Analyst (963)

American Builders and Contractors Supply Co•Beloit, WI

About The Position

The Data Analyst – Data Quality & Governance is responsible for defining, documenting, and enabling enterprise data standards, quality rules, and governance processes across master data domains. This role partners with business stakeholders, subject matter experts (SMEs), IT teams, and the Enterprise MDM Technical Lead to translate business needs into clear data standards and actionable quality rules. The analyst plays a critical role in ensuring data is accurate, consistent, and fit for purpose by defining validation rules, monitoring data quality metrics, and supporting audit and exception reporting. This position combines strong analytical thinking, business acumen, and communication skills to drive adoption of data governance practices and continuous improvement in data quality.

Requirements

3–5+ years of experience in data analysis, data governance, or data quality roles.
Strong understanding of data quality concepts (accuracy, completeness, consistency, timeliness, uniqueness).
Experience defining data standards, business rules, and governance processes.
Experience working with data quality reporting, exception management, and KPIs.
Strong analytical and problem-solving skills.
Ability to translate business requirements into structured data rules and definitions.
Experience working with cross-functional teams (business + IT).
Strong communication and documentation skills.

Nice To Haves

Bachelor’s degree in Data Analytics, Mathematics, Information Systems, Computer Science, Business, or a related field.
Experience working with Master Data Management (MDM) or PIM platforms (Stibo preferred).
Experience supporting multiple data domains (Product, Customer, Vendor, Location).
Familiarity with data governance frameworks and stewardship models.
Experience working with data visualization or reporting tools (e.g., Power BI).
Strong interpersonal and facilitation skills.
Ability to organize and clearly define complex data concepts.
Detail-oriented with a focus on accuracy and consistency.
Business-mindset with the ability to connect data to operational outcomes.
Curious and proactive in identifying data issues and improvement opportunities.
Ability to influence without authority across business and technical teams.
Structured thinker with strong documentation discipline.

Responsibilities

Define, document, and maintain enterprise data standards, definitions, and business rules.
Partner with business users and SMEs to gather requirements and translate them into clear, actionable data policies.
Document data governance processes, workflows, and stewardship responsibilities.
Ensure alignment of data standards across domains (Product, Customer, Vendor, Location, etc.).
Define data quality rules, validations, and thresholds based on business requirements.
Partner with the Enterprise MDM Technical Lead to implement and enhance rules within the Stibo platform.
Continuously evaluate and refine rules to improve effectiveness and usability.
Support the design of real-time validation and data entry controls.
Define, develop, and maintain data quality audit reports and scorecards.
Identify, analyze, and track data exceptions and anomalies.
Establish KPIs and metrics to measure data quality performance.
Provide insights and recommendations to improve data accuracy and completeness.
Develop and execute test scenarios for data quality rules and governance processes.
Validate rule effectiveness and ensure alignment with business intent.
Support user acceptance testing (UAT) for new rules, workflows, and enhancements.
Partner with business stakeholders, IT, and data owners to drive adoption of data governance practices.
Facilitate discussions to align on definitions, rules, and data ownership.
Act as a liaison between business and technical teams.
Support training and communication efforts related to data standards and quality expectations.
Identify opportunities to improve data quality processes and governance frameworks.
Recommend enhancements to tools, reporting, and workflows.
Support ongoing maturity of enterprise MDM capabilities.