Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren's reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company's brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world's most widely recognized families of consumer brands.

At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.

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Purpose & Scope

The Associate Data Governance and Quality Manager is an individual contributor role — hands-on, with no direct reports — sitting within a growing data governance function at Ralph Lauren. The role is a foundational hire: as Ralph Lauren advances its global ERP and data platform transformation, this position helps build the governance and data quality controls that make that transformation trustworthy and durable.

Working closely with Data Engineering, Architecture, Data Product Management, and business stakeholders, the role owns the day-to-day execution of data quality monitoring, metadata management, and governance process support across the enterprise data estate.

The role is weighted toward either data quality operations or data catalogue and metadata management depending on team need at the point of hire — both profiles are welcomed, and the successful candidate will bring depth in one and working familiarity with the other.

This is not a management or oversight role. It is a practitioner role for someone who wants to do the work directly, build something that matters, and grow with the function.

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Responsibilities

Data Quality Monitoring & Resolution
Own the data quality control surface across key data products and pipelines.
Define, implement, and monitor automated data quality rules and checks using Soda or equivalent tooling.
Investigate data quality issues, identify root causes, and coordinate resolution with Data Engineering teams.
Track data quality metrics and trends, and report on improvements or emerging risks.
Maintain a clear backlog of known data issues, prioritized by business impact.
Metadata, Cataloging & Lineage
Own the integrity of metadata, glossary, and lineage in the enterprise data catalogue.
Maintain and improve metadata, business glossary entries, and data lineage in Atlan or equivalent catalogue platform.
Partner with Data Engineering and Product teams to ensure new data assets are properly cataloged, documented, and assigned ownership.
Support discoverability of data assets by ensuring descriptions, classifications, and ownership information are current and maintained to a documented standard.
Governance Process Support
Support the execution of data governance policies, standards, and controls across data domains.
Help coordinate data stewardship activities, including issue triage and resolution workflows.
Support audits and compliance reviews by providing evidence of governance and quality controls.
Identify and surface gaps in governance coverage across new or evolving data products.
Stakeholder Collaboration & Enablement
Work with Data Product Managers and Analysts to clarify data definitions and quality expectations.
Provide guidance to data consumers on interpreting metadata, lineage, and quality indicators.
Communicate clearly on data quality status, issues, and remediation progress to stakeholders.
Works across Data Engineering, Architecture, and business teams to embed data quality and governance controls.
Contribute to training and documentation that raises governance and quality awareness across teams.

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Qualifications

Required

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field. Master's degree preferred.
4–7+ years of experience in data governance, data quality, data management, or related analytical roles.
Hands-on experience with data quality tooling: Soda, or equivalent (Great Expectations, Monte Carlo, Collibra DQ, Informatica DQ, Anomalo, Ataccama).
Experience with data catalogue and metadata platforms: Atlan, or equivalent (Collibra, Alation, Purview, Informatica EDC).
Strong SQL skills, with the ability to investigate and validate data quality issues directly.
Strong grasp of data quality dimensions (completeness, validity, consistency, timeliness) and root-cause analysis.
Experience maintaining business glossaries, lineage, and ownership metadata to a documented standard.

Preferred

Experience working with enterprise data platforms such as Databricks and Azure.
Familiarity with data privacy, compliance, or regulatory requirements relevant to enterprise data.
Familiarity with data classification and sensitivity labelling.
Experience in retail, consumer goods, or other data-intensive industries.
Exposure to Power BI or other BI tools from a governance and quality perspective.

Success Measures

Growing coverage and reliability of automated data quality checks across priority data products.
Faster identification and resolution of data quality issues.
Improved completeness and accuracy of metadata, lineage, and catalogue documentation.
Positive stakeholder feedback on governance support and responsiveness.

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