Role Summary
American Express is seeking a highly technical Senior Associate – CyberOps & Assurance to join our Data Security Posture Management (DSPM) and Data Discovery & Classification engineering team.
This role is responsible for hands-on implementation, configuration, and integration of enterprise data security platforms across a complex, hybrid data ecosystem. You will focus on building scalable capabilities to discover, classify, and protect sensitive data, while integrating these platforms into broader enterprise systems such as data catalogs and IT asset management (ITAM).
This is a deep technical individual contributor role requiring strong engineering expertise, systems thinking, and the ability to operationalize data security at scale. The role also leverages modern automation and AI-assisted capabilities to improve efficiency and detection quality, including in emerging AI-driven data environments.
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 our 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.
Responsibilities:
Key Responsibilities
Platform Implementation & Engineering
- Design, implement, and configure enterprise data discovery, classification, and DSPM platforms across multi-cloud and on-prem environments
- Develop scalable onboarding patterns for structured and unstructured data sources (databases, data lakes, SaaS platforms, file systems)
Integration & Data Flow Engineering
- Engineer integrations between DSPM/classification platforms and downstream enterprise systems, including:
- Data catalog platforms
- ITAM / CMDB systems
- SIEM / security analytics platforms
- Build API-driven and event-based data flows to enable consistent propagation of classification and risk signals
Data Discovery, Classification & Control Enablement
- Define and implement classification schemas for sensitive data (PCI, PII, financial, regulated data)
- Tune detection logic and classification rules to improve accuracy and reduce false positives
- Translate policy and regulatory requirements into scalable technical controls
- Extend discovery and classification capabilities into next-generation data creation environments, 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 visibility and control over sensitive data created, transformed, or exposed in these environments
Automation & Operationalization
- Build automation for data onboarding, scanning, classification workflows, and remediation processes
- Develop reusable patterns, scripts, and runbooks to improve operational efficiency and consistency
- Leverage AI-assisted automation tools and platform-native intelligence to streamline workflows, reduce manual intervention, and accelerate response and remediation activities
- Identify opportunities to apply AI-driven approaches to scale operations, improve process efficiency, and enhance consistency in control execution
AI-Enabled Enhancements (Practical Application)
- Leverage built-in platform intelligence and AI-assisted capabilities to improve data discovery and classification outcomes
- Utilize AI-assisted development tools to accelerate engineering tasks and reduce manual effort
- Contribute to improving signal quality through iterative tuning and data-driven feedback loops
Cross-Functional Collaboration
- Partner with data engineering, platform, and governance teams to embed security into data lifecycles
- Support audit and compliance efforts through accurate data visibility and reporting
Qualifications:
Required Qualifications
- 4 to 8 years of experience in cybersecurity, data security, or data engineering with strong focus on data discovery, classification, or DSPM
- Hands-on experience implementing and configuring enterprise data security platforms (tool-flexible mindset required)
- Strong understanding of:
- Modern data architectures (data lakes, warehouses, distributed systems)
- Structured and unstructured data environments
- Data classification techniques and regulatory requirements (PCI, PII)
- Proven experience integrating platforms with:
- Data catalogs (e.g., Collibra, Alation or similar)
- ITAM / CMDB systems
- SIEM or security analytics platforms
- Strong technical skills in:
- APIs and integration patterns (REST, event-driven architectures)
- Programming/scripting (Python, Java, or similar)
- Cloud platforms (AWS, Azure, or GCP)
- Demonstrated experience leveraging AI-assisted tools or platform-native intelligence to enhance engineering productivity or improve data discovery/classification outcomes
- Ability to apply data-driven approaches (including AI/ML-assisted techniques) to improve detection accuracy, reduce false positives, and scale security operations
Preferred Qualifications
- Experience with DSPM or data security platforms such as BigID, Securiti, Varonis, Spirion, or similar
- Familiarity with metadata management and data governance ecosystems
- Experience in financial services or other highly regulated environments
- Exposure to automation frameworks, DevSecOps, or infrastructure-as-code practices
- Experience working with or tuning ML/NLP-based classification capabilities
- Exposure to securing AI/ML or GenAI-driven data environments
Leadership & Mindset Expectations
- Strong engineering mindset with a focus on scalability, automation, and integration
- Systems thinker who understands end-to-end data flows, not just point solutions
- Ability to operate independently while collaborating across multiple teams
- Practical, outcome-oriented approach to leveraging AI and automation to improve efficiency and quality
Why This Role Matters
This role is foundational to building a modern, scalable data security program at American Express. You will directly contribute to how sensitive data is discovered, classified, and protected across both traditional and emerging AI-driven data ecosystems, enabling secure innovation across the enterprise.
ORMCM
Guardian
