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Director, Software Engineering
American Express. Own the strategy, roadmap, and execution for Servicing Data Platforms, including DaaS, MaaS, operational data engineering, operational reporting platforms, Customer Journey Intelligence Engine, data ingestion platforms, and data lake modernization .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in leading enterprise-scale data platform engineering, focusing on cloud-native architectures, data governance, and operational excellence. Proven ability to drive platform modernization strategies and build high-performing engineering teams while ensuring compliance and data quality.
Highest-signal resume keywords
Cloud-Native Data PlatformsData as a Service (DaaS)Metrics as a Service (MaaS)Enterprise Data GovernanceAI-Ready Data Foundations
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringData Ingestion PlatformsOperational ReportingReal-Time Data ArchitecturesData FederationMetadata ManagementData QualityMachine LearningGenerative AIEvent-Driven Architectures
Soft Skills
Exceptional CommunicationExecutive InfluencingPeople LeadershipMentoringCollaboration
Tools & Technologies
APIsStreaming TechnologiesDistributed SystemsData LakesIntelligence Access Layers
Industry Keywords
Cloud TransformationOperational ExcellenceData Lifecycle ManagementSelf-Service AnalyticsContinuous Improvement
Tech Stack
Tools & technologiesCloudDistributed Systems
About the role
Key responsibilities & impact- Own the strategy, roadmap, and execution for Servicing Data Platforms, including DaaS, MaaS, operational data engineering, operational reporting platforms, Customer Journey Intelligence Engine, data ingestion platforms, and data lake modernization
- Define and execute multi-year platform modernization strategies aligned to cloud-first and AI-enabled enterprise objectives
- Drive platform simplification, standardization, reuse, scalability, resiliency, availability, performance, and operational excellence
- Lead engineering teams responsible for platform development, reliability, automation, and lifecycle management
- Build and evolve trusted, accessible, reusable, and consumable servicing data capabilities
- Establish enterprise patterns for data federation, metadata management, lineage, cataloging, context propagation, and reusable intelligence services
- Enable real-time and near-real-time servicing data access through governed APIs, event-driven architectures, and intelligence access layers
- Drive adoption of DaaS and MaaS across business and technology organizations
- Embed governance, privacy, security, compliance, data quality, retention, auditability, and access controls into platform architecture and engineering practices
- Lead reusable intelligence components and foundational services supporting AI, analytics, automation, customer intelligence, GenAI, agentic systems, and decisioning
- Evaluate emerging AI and data technologies and establish adoption strategies
- Own the servicing operational reporting ecosystem and establish consistent metrics, KPIs, and measurement frameworks
- Drive self-service reporting, real-time intelligence, self-service analytics, and reusable reporting frameworks
- Translate data into actionable decisions and measurable business outcomes with business and operational leaders
- Build and lead a high-performing engineering organization
- Develop talent through coaching, mentoring, succession planning, and technical leadership development
- Establish engineering operating models, delivery practices, and quality standards
- Lead cross-functional partnerships across Product, Technology, Enterprise Architecture, Operations, Risk, and Vendor organizations
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or a related technical discipline; advanced degree preferred
- 10+ years of progressive software engineering and technology experience, including significant experience leading large-scale engineering teams and enterprise technology platforms
- Experience leading enterprise-scale data platform engineering organizations with end-to-end accountability for strategy, architecture, engineering execution, platform reliability, and operational excellence
- Expertise in cloud-native data platforms, distributed systems, data lakes, and large-scale data ecosystems
- Experience defining and executing multi-year platform modernization and cloud transformation strategies
- Experience with Data as a Service, Metrics as a Service, reusable data products, intelligence access layers, data ingestion platforms, and governed APIs
- Knowledge of data ingestion and processing, data federation, metadata management, data quality, lineage, cataloging, master data management, and enterprise data lifecycle management
- Understanding of real-time and near-real-time data architectures, event-driven systems, streaming technologies, APIs, distributed processing, and operational reporting platforms
- Experience building enterprise-scale operational reporting and analytics capabilities, standardized metrics and KPIs, self-service analytics, real-time intelligence, and reusable reporting frameworks
- Experience establishing AI-ready data foundations supporting advanced analytics, machine learning, Generative AI, customer intelligence, agentic systems, automation, and intelligent decisioning
- Understanding of AI/ML and Generative AI ecosystems, including LLMs, RAG, vector databases, semantic search, knowledge management, context engineering, and reusable AI/intelligence services
- Ability to evaluate emerging data, cloud, AI, and GenAI technologies and establish enterprise adoption strategies
- Knowledge of enterprise data governance, security, privacy, risk, and regulatory requirements
- Ability to establish engineering standards and operating models improving software quality, delivery velocity, availability, resiliency, performance, observability, and operational effectiveness
- Ability to partner across Product, Technology, Data Science, Enterprise Architecture, Information Security, Risk, Compliance, Operations, and business organizations
- Strong business and technology acumen
- Exceptional communication and executive-influencing skills
- Proven people leadership experience building, developing, mentoring, and scaling high-performing engineering organizations
- Ability to lead through influence across complex, matrixed organizations
- Commitment to engineering excellence and continuous improvement
Benefits
Comp & perks- Competitive base salaries
- Bonus incentives
- Support for financial well-being and retirement
- Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location)
- Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
- Generous paid parental leave policies (depending on your location)
- 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