Director - Data Governance & Management: Data Quality

The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.

This role is part of the newly formed Enterprise Technology Services (ETS) Data Office.

The Director, Data Quality (DQ) will lead the strategy and execution of enterprise Data Quality capabilities across ETS. This role is responsible for modernizing how data quality risk is measured, monitored, and remediated while establishing scalable controls that improve trust in data used for operations, analytics, AI, regulatory processes, and decision-making. This leader will build a proactive, AI-enabled Data Quality practice focused on prevention over detection, automation over manual effort, and measurable business outcomes over compliance-driven activities.

Primary Responsibilities:

• Define and execute the enterprise Data Quality strategy across ETS aligned to industry-leading data management and risk frameworks. 
• Standardize Data Quality measurement and monitoring across critical data domains, including data at rest, in motion, and at point of entry. 
• Establish scalable Data Quality controls and governance practices that reduce operational, regulatory, and customer risk. 
• Lead enterprise root-cause analysis and remediation efforts to reduce recurring data issues and improve control effectiveness. 
• Build AI-enabled capabilities for anomaly detection, intelligent monitoring, automated profiling, and predictive Data Quality insights. 
• Modernize Data Quality reporting through automated dashboards, drill-down analytics, and executive-ready risk transparency. 
• Partner with Data Stewards, Product Owners, Engineering, Risk, and Control Management teams to ensure data is fit for purpose across business processes and platforms. 
• Drive consistent Data Concern, Issue, and Event Management practices while improving remediation speed and reducing repeat failures. 
• Define KPIs and risk metrics that demonstrate Data Quality health, control performance, and business impact. 
• Translate Data Quality investments into measurable business value including operational efficiency, risk reduction, and improved decision-making.

• 10+ years of direct work experience in large scale/enterprise data projects, with at least 4 years of direct experience relating to creation and execution of formal data governance and/or data management programs
• Deep expertise in enterprise Data Quality, Data Governance, and Data Risk Management within large-scale or highly regulated environments. 
• Strong understanding of industry frameworks such as DCAM, DAMA-DMBOK, BCBS 239, and modern Data Product/Data Mesh principles. 
• Proven experience building enterprise-scale Data Quality programs and operating models. 
• Demonstrated expertise leveraging AI and machine learning to modernize Data Quality operations and automation. 
• Experience implementing Data Quality controls, metrics, monitoring, and remediation practices across complex data ecosystems. 
• Strong executive communication and stakeholder management skills with ability to simplify complex data topics for business and technology leaders. 
• Proven ability to lead enterprise transformation initiatives across federated organizations.