Gap Inc.
About the Role
We are seeking a high-impact techno-functional Data Quality (DQ) Manager to lead and operationalize our DG-driven Enterprise DQ strategy initiatives. This role combines technical expertise in AI/ML, Python, DQ, and data visualization with a business-focused approach across the Merchandising Product Lifecycle, Financial Forecast Planning, Omnichannel Commerce, and Enterprise Reporting, covering core data assets across finance, product, customer, inventory, and supply chain domains. You will serve as a strategic leader to align data governance with engineering solutions, building scalable frameworks, meaningful rules, and dashboards that inform global retail decisions. The role requires mastery in AI/ML, Python, and visualization, along with a strong understanding of business operations in Product Lifecycle, Finance, and Omnichannel Reporting. Ensuring data quality standards meet technical benchmarks and are relevant to business needs is essential. You will embed DQ controls throughout data processes to deliver actionable insights that promote data accuracy, trust, and interoperability enterprise-wide. What You'll Do
Lead the design, integration, and execution of our Data Quality strategy based on Enterprise DG principles and Data Management capabilities. Collaborate with DG teams to translate business requirements into technical solutions for AI-powered automation, validation, anomaly detection, and ongoing monitoring. Architect and deploy AI/ML models to automate DQ checks across retail domains like finance, inventory, pricing, and promotions. Develop Python scripts and metadata pipelines integrated with governance tools such as data catalogs, dashboards, and quality scoring systems. Operationalize DQ rules for critical domains including Product Lifecycle Management, Financial Planning, Customer Journeys, and Omnichannel Commerce. Create visually rich dashboards using Power BI or Tableau for various teams to facilitate decision-making. Coordinate with DG stewards, SMEs, and tech teams to ensure consistent application of DQ policies and rules. Monitor KPIs to evaluate DQ impact on business processes and forecast accuracy. Who You Are
A strategic thinker with a comprehensive view of the data ecosystem from acquisition to consumption. An innovator eager to integrate governance, DQ automation, and visual storytelling to build data trust. Engaged in understanding business needs to ensure data quality supports retail agility. Excellent communicator capable of presenting DQ initiatives to leadership. Possesses technical rigor and literacy in data quality for both technical and business stakeholders. A collaborative team player bridging technical and non-technical teams. Thrives in fast-paced, goal-oriented environments. Strong analytical skills to identify data patterns, troubleshoot, and propose solutions. Bachelor’s or Master’s in Computer Science, Data Analytics, or related field. 5+ years in Lead Data Quality roles, preferably in Retail, CPG, or B2C eCommerce. Expertise with DQ tools like Monte Carlo and Informatica DQ, and knowledge of DQ principles and best practices. Experience with Data Governance platforms (Collibra, Atlan, Alation) and Data Management frameworks with ServiceNow integration. Advanced Python skills for scripting, automation, and metadata enrichment. Experience using AI/ML for retail intelligence, predictive modeling, and automation. Proficiency in data visualization tools such as Power BI, Tableau, or Miro. Proficiency in SQL, relational databases, and cloud data warehouses (Azure, GCP, AWS). Strong understanding of Retail Product Lifecycle Management and Finance Performance Metrics.
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We are seeking a high-impact techno-functional Data Quality (DQ) Manager to lead and operationalize our DG-driven Enterprise DQ strategy initiatives. This role combines technical expertise in AI/ML, Python, DQ, and data visualization with a business-focused approach across the Merchandising Product Lifecycle, Financial Forecast Planning, Omnichannel Commerce, and Enterprise Reporting, covering core data assets across finance, product, customer, inventory, and supply chain domains. You will serve as a strategic leader to align data governance with engineering solutions, building scalable frameworks, meaningful rules, and dashboards that inform global retail decisions. The role requires mastery in AI/ML, Python, and visualization, along with a strong understanding of business operations in Product Lifecycle, Finance, and Omnichannel Reporting. Ensuring data quality standards meet technical benchmarks and are relevant to business needs is essential. You will embed DQ controls throughout data processes to deliver actionable insights that promote data accuracy, trust, and interoperability enterprise-wide. What You'll Do
Lead the design, integration, and execution of our Data Quality strategy based on Enterprise DG principles and Data Management capabilities. Collaborate with DG teams to translate business requirements into technical solutions for AI-powered automation, validation, anomaly detection, and ongoing monitoring. Architect and deploy AI/ML models to automate DQ checks across retail domains like finance, inventory, pricing, and promotions. Develop Python scripts and metadata pipelines integrated with governance tools such as data catalogs, dashboards, and quality scoring systems. Operationalize DQ rules for critical domains including Product Lifecycle Management, Financial Planning, Customer Journeys, and Omnichannel Commerce. Create visually rich dashboards using Power BI or Tableau for various teams to facilitate decision-making. Coordinate with DG stewards, SMEs, and tech teams to ensure consistent application of DQ policies and rules. Monitor KPIs to evaluate DQ impact on business processes and forecast accuracy. Who You Are
A strategic thinker with a comprehensive view of the data ecosystem from acquisition to consumption. An innovator eager to integrate governance, DQ automation, and visual storytelling to build data trust. Engaged in understanding business needs to ensure data quality supports retail agility. Excellent communicator capable of presenting DQ initiatives to leadership. Possesses technical rigor and literacy in data quality for both technical and business stakeholders. A collaborative team player bridging technical and non-technical teams. Thrives in fast-paced, goal-oriented environments. Strong analytical skills to identify data patterns, troubleshoot, and propose solutions. Bachelor’s or Master’s in Computer Science, Data Analytics, or related field. 5+ years in Lead Data Quality roles, preferably in Retail, CPG, or B2C eCommerce. Expertise with DQ tools like Monte Carlo and Informatica DQ, and knowledge of DQ principles and best practices. Experience with Data Governance platforms (Collibra, Atlan, Alation) and Data Management frameworks with ServiceNow integration. Advanced Python skills for scripting, automation, and metadata enrichment. Experience using AI/ML for retail intelligence, predictive modeling, and automation. Proficiency in data visualization tools such as Power BI, Tableau, or Miro. Proficiency in SQL, relational databases, and cloud data warehouses (Azure, GCP, AWS). Strong understanding of Retail Product Lifecycle Management and Finance Performance Metrics.
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