Manager - Data Governance & Management

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.

As a Data Governance & Management Senior Manager, you are part of a team responsible for enabling compliance with the Enterprise Data Management Operating Policy within the Enterprise Technology Services (ETS) business unit. You will help establish and mature data governance capabilities that enable trusted, high-quality, well-governed data to support business operations, regulatory compliance, analytics, and AI-driven innovation.

You and your team are responsible for identifying critical data, maintaining business metadata and data definitions, classifying data, supporting data sourcing and usage requests, assessing data risk, measuring Data Risk Controls, and ensuring Data Incidents are effectively remediated. You will partner across business units, technology organizations, product teams, and enterprise data organizations to define and implement scalable data governance strategies that improve data quality, transparency, operational efficiency, and regulatory compliance. 

You will also champion the adoption of AI-enabled governance capabilities and intelligent automation, identifying opportunities to automate manual governance activities, improve data observability, accelerate issue resolution, and enhance decision-making while ensuring responsible AI practices and appropriate governance controls.

• Support ETS by identifying data risk, performing root-cause analysis of data incidents, and driving timely remediation of audit findings, regulatory observations, and control deficiencies.
• Develop deep expertise in the Enterprise Data Management Operating Policy and translate enterprise standards into practical governance processes and operating procedures for ETS.
• Lead holistic platform data quality monitoring, including development and oversight of key data quality metrics, scorecards, dashboards, and proactive monitoring capabilities.
• Drive identification and assessment of data risk by partnering with upstream data providers, downstream consumers, technology teams, and business stakeholders.
• Partner with Process Owners and Data Custodians to design, implement, test, and continuously improve automated data quality controls and preventative data risk controls.
• Lead cross-functional coordination to ensure complete, accurate, and sustainable system-level lineage, metadata, and business glossary documentation across enterprise platforms.
• Build deep platform expertise to identify Critical Data Elements (CDEs), define governance priorities, and influence long-term data management roadmaps.
• Partner with Data Governance & Management leadership to define and execute the strategic data governance roadmap, supporting enterprise modernization and data product initiatives.
• Collaborate with Product Managers, Engineering teams, and Architecture partners to ensure new products, platforms, and capabilities are designed with governance, quality, lineage, privacy, and regulatory requirements embedded from inception.
• Identify opportunities to improve governance processes through intelligent automation, workflow optimization, and AI-assisted capabilities that reduce manual effort while strengthening governance outcomes.
• Leverage AI-powered analytics and automation tools to accelerate metadata discovery, lineage validation, data quality monitoring, policy adherence, issue triage, documentation generation, and governance reporting.
• Partner with enterprise AI, Risk, Compliance, Legal, and Information Security teams to ensure governance practices support responsible AI adoption, model transparency, data usage controls, and regulatory expectations.
• Develop governance metrics, KPIs, and executive reporting that provide actionable insights into data quality, control effectiveness, operational efficiency, and governance maturity.
• Foster a culture of continuous improvement by evaluating emerging technologies, AI capabilities, and automation opportunities that enhance data management effectiveness while maintaining strong governance standards.

 

• 5+ years of experience executing data governance and data management responsibilities in a regulated or risk-managed environment (e.g., regulatory reporting, risk management, financial services)
• Strong communication skills and ability to influence and engage at multiple levels and cross functionally
• Ability to work independently and influence stakeholders
• Strong understanding of Data Management and Data Governance concepts (metadata, lineage, data quality, business glossary, data risk and incident management, etc.) and prior experience
• Prior experience with system or data analysis
• Experience applying Generative AI and AI-assisted productivity tools to improve governance processes, documentation, metadata management, reporting, or operational efficiency.
• Experience identifying opportunities to automate manual governance activities using AI, scripting, workflow automation, APIs, or low-code/no-code platforms.
• Understanding of AI governance principles including responsible AI, model transparency, explainability, data privacy, bias mitigation, and regulatory considerations.
• Prior experience with risk management, including control assessment and creation preferred
• Intermediate competency in SQL, BigQuery, Python or other programming languages
• Experience using AI copilots (e.g., GitHub Copilot, Microsoft Copilot, ChatGPT Enterprise, Gemini, or equivalent enterprise AI platforms) to improve engineering, documentation, governance, and analytical workflows while adhering to enterprise security and compliance requirements.
• Prior experience in Technology risk, IT governance or Technology Data Management preferred
• Prior experience with Agile or SAFe project methodologies
• Prior experience of data governance, metadata, and data lineage tools such as Collibra, MANTA, etc.
• Bachelor's degree in finance, Engineering, Mathematics, Statistics, Computer Science, or other similar fields