Manager - Product Management (Data Security)

American Express•Phoenix, AZ

1d•Hybrid

About The Position

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. Role Summary American Express is seeking an experienced Manager, Product Management to lead the strategy, roadmap, and delivery of a portfolio of enterprise data security capabilities. This role is responsible for defining and evolving a cohesive product strategy across key data security domains, including: Encryption (payment and non-payment) Data Security Posture Management (DSPM) Data Activity Management (DAM) Data Loss Prevention (DLP) You will operate at the intersection of security, data, and technology, driving alignment across engineering, risk, compliance, and business stakeholders. This role requires a strong product mindset, the ability to manage complex capability portfolios, and a deep understanding of how to deliver scalable, measurable security outcomes.

Requirements

15+ years of experience in product management, cybersecurity, or technology leadership, with a strong track record of delivering complex enterprise capabilities
Demonstrated experience managing product portfolios or multi-capability programs within cybersecurity, infrastructure, or data domains
Strong understanding of: Data security domains (encryption, DSPM, DAM, DLP) Data architectures and data lifecycle management Regulatory and compliance considerations (e.g., PCI, data protection)
Proven ability to: Define product strategy and translate it into executable roadmaps Align and influence senior stakeholders across technical and non-technical teams Drive delivery in complex, matrixed organizations
Experience working closely with engineering teams and understanding technical trade-offs and implementation considerations
Demonstrated experience defining and operationalizing KPIs and KRIs, particularly those tied to risk reduction, control effectiveness, and platform adoption
Demonstrated ability to incorporate AI-driven capabilities or considerations into product strategy, particularly related to data security, automation, or analytics

Nice To Haves

Experience in financial services or other highly regulated industries
Experience managing security or data platforms at enterprise scale
Familiarity with modern data security approaches such as DSPM and data-centric security models
Experience defining or evolving product operating models within large organizations
Exposure to securing or enabling AI/ML or GenAI-driven use cases
Experience working with metrics-driven product management and risk quantification approaches
Strong product mindset with focus on outcomes, not just deliverables
Ability to think in terms of capabilities, platforms, and ecosystems rather than individual tools
Deep commitment to measurable impact through KPIs and KRIs
Excellent stakeholder management and influence skills
Structured, data-driven decision-making approach
Forward-looking perspective on emerging technologies and risks, including AI

Responsibilities

Define and maintain a clear product vision and strategy for enterprise data security capabilities
Develop and manage a multi-year roadmap aligned to organizational priorities, regulatory requirements, and emerging risks
Evolve the portfolio toward modern, data-centric security models, including DSPM and AI-driven environments
Manage a portfolio of data security capabilities across encryption, DSPM, DAM, and DLP
Define capability boundaries, integration points, and end-to-end operating models
Ensure alignment and interoperability across capabilities to avoid fragmentation and duplication
Define, implement, and continuously refine key performance indicators (KPIs) and key risk indicators (KRIs) across the data security portfolio
Establish measurable outcomes across core dimensions, including: Coverage & Visibility (e.g., %25 of sensitive data discovered and classified) Control Effectiveness (e.g., reduction in exception rates for unprotected sensitive data) Operational Efficiency (e.g., time to detect and remediate data security issues) Adoption & Consumption (e.g., increase in usage of DSPM, DAM, DLP capabilities across the enterprise)
Drive improvement in critical metrics such as: Reduction in data security exception rates (e.g., unencrypted, unmonitored, or non-compliant sensitive data) Increase in capability consumption and integration rates across applications and platforms
Partner with engineering and risk teams to ensure metrics are: Technically measurable and reliable Aligned to actual risk reduction (not just activity) Reportable at both operational and executive levels
Develop and maintain executive-level dashboards and reporting to track progress, highlight risks, and inform prioritization
Partner with engineering, cybersecurity, data, risk, compliance, and business teams to define requirements and priorities
Drive alignment across diverse stakeholders with competing priorities
Translate regulatory and risk requirements into actionable product capabilities and measurable outcomes
Define and manage product backlogs, priorities, and success criteria
Partner closely with engineering teams to ensure effective and timely delivery
Ensure all product initiatives are tied to clearly defined KPIs/KRIs and measurable impact
Drive evolution of data security capabilities to address next-generation data creation and usage patterns, including: LLM-driven workflows and prompt/response data flows AI/ML pipelines and model training datasets Emerging platforms such as MCP servers and AI orchestration layers
Ensure product strategy accounts for new data risks introduced by AI and advanced analytics, and that these risks are incorporated into KPI/KRI frameworks
Establish and mature a product operating model for data security capabilities
Drive continuous improvement in prioritization, delivery, and stakeholder engagement
Promote a culture of outcome-driven product management, focusing on measurable risk reduction and capability adoption

Benefits

Competitive base salaries
Bonus incentives
6%25 Company Match on retirement savings plan
Free financial coaching and financial well-being support
Comprehensive medical, dental, vision, life insurance, and disability benefits
Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
Free and confidential counseling support through our Healthy Minds program
Career development and training opportunities