Data Quality - Lead Specialist

About the Role

We are seeking a high-impact techno-functional Data Quality (DQ) Manager to lead the charge and operationalize our DG-driven Enterprise DQ strategy initiatives—harmonizing technical ingenuity with retail business depth— to shape data standards, drive performance, and unlock value across the organization.

This role blends deep, hands-on technical skills in AI/ML, Python, DQ and data visualization with a business-first mindset across the Merchandising Product Lifecycle, Financial Forecast Planning, Omnichannel Commerce and Enterprise Reporting that encompasses core critical data assets (CDEs) across business domains that span finance, product, customer, inventory, and supply chain business unit operations.

You will serve as a strategic catalyst to unify data governance objectives with engineering solutions —building frameworks that scale, rules that matter, DQ governance dashboards that tell the story and shape our global retail decisions.
You will blend technical mastery in AI/ML, Python, and data visualization with a strong understanding of business function operations along the end-to-end Product Lifecycle, Finance, and Omnichannel Reporting.

You will ensure that our data quality standards not only meet rigorous technical benchmarks but are anchored in business relevance across Product Lifecycle, Finance, eCommerce, Store Operations, and Inventory Management. You will be instrumental in embedding DQ controls from data acquisition to consumption to deliver clear, actionable insights across business units promoting data accuracy, trust, reliability, and dq interoperability across the Enterprise.

What You'll Do

• Lead the design, integration and execution of our Data Quality strategy rooted in Enterprise DG principles and Data Management capabilities (e.g. dg policy, business/technical metadata CDEs, data lineage, data integration &, interoperability).
• Partner with DG teams to translate business requirement rules into technical specifications for solutioning AI-powered automation, validation, anomaly detection, continuous monitoring & remediation integrating DQ with ServiceNow, Enterprise DQ dashboards and DG Catalog Platform Tools.
• Architect and deploy AI/ML models to automate end-to-end DQ checks (e.g., technical/operational and business rules) across retail business domain functions: finance, inventory, pricing, promotions, assortment, vendor transaction records working with best-in-class DQ and DG Tooling
• Develop Python-based scripts and metadata enrichment pipelines integrated with governance tooling (e.g., data catalog, DQ dashboards, quality scoring systems).
• Operationalize DQ rule sets tied to critical domains including Retail Product Lifecycle Management, Financial Planning & Analysis, Customer Journeys, and Omnichannel Commerce.
• Deliver visually rich and actionable insights through Power BI/Tableau dashboards tailored to executive, merchandising, and finance teams.
• Facilitate collaboration between DG stewards, domain SMEs, and technology teams to ensure consistent interpretation and enforcement of DQ rules & policies.
• Monitor KPIs that measure DQ impact on business processes and forecast accuracy.

Who You Are

• You are a strategic thinker that see’s the big picture across the data ecosystem —from data acquisition to transformation to consumption and how it powers business decisions
• You are an innovator with a strong drive to integrate governance with dq automation, and visual storytelling to champion data trust
• You are engaged and eager to learn the business to help it run smarter ensuring data quality fuels retail agility
• Excellent communication skills comfortable with defining, implementing & presenting DQ initiatives to Leadership
• You bring both technical rigor and data quality literacy to both business data and technical conversations
• You have a collaborative mindset bridging the gap between technical and non-technical teams
• You thrive in fast-paced goal-focused environments
• You have excellent analytical skills to identify data patterns, troubleshoot issues, and propose effective solutions.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Analytics, Business Intelligence, or related field
• 5+ years in Lead Data Quality roles, preferably within Retail, CPG, or B2C eCommerce environments
• DQ Expertise with best-in-class DQ Tools (Monte Carlo, Informatica DQ) and in-depth knowledge of DQ principles methodologies & best practices.
• Experience with Data Governance industry Platform Tools (Collibra, Atlan, Alation) & Data Management Frameworks with ServiceNow DQ workflow integration
• Advanced proficiency in Python building scripts for dq automation