Director of Software Engineering – Data Engineering, Metadata Management, Generative AI, DaaS, MaaS

American Express

. Own strategy, roadmap, and execution for Servicing Data Platforms, including DaaS, MaaS, operational data engineering, reporting platforms, Customer Journey Intelligence Engine, data ingestion platforms, and data lake modernization .

Posted 10/7/2026full-timeChennai • IndiaLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading enterprise-scale data platform engineering, focusing on cloud-native solutions, data governance, and operational excellence. Proven ability to drive platform modernization strategies and build high-performing engineering teams through effective leadership and collaboration.

Highest-signal resume keywords

Cloud-Native Data PlatformsData as a Service (DaaS)Metrics as a Service (MaaS)AI-Ready Data FoundationsEnterprise Data Governance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringData IngestionData FederationMetadata ManagementOperational ReportingReal-Time Data ArchitecturesEvent-Driven SystemsMachine LearningGenerative AIDistributed Systems

Soft Skills

Exceptional CommunicationExecutive InfluencingPeople LeadershipMentoringContinuous Improvement

Tools & Technologies

APIsStreaming TechnologiesData LakesIntelligence Access LayersReusable Reporting Frameworks

Industry Keywords

Cloud TransformationOperational ExcellenceData QualityRisk ManagementCompliance

Tech Stack

Tools & technologies

CloudDistributed Systems

About the role

Key responsibilities & impact

Own strategy, roadmap, and execution for Servicing Data Platforms, including DaaS, MaaS, operational data engineering, reporting platforms, Customer Journey Intelligence Engine, data ingestion platforms, and data lake modernization
Define and execute multi-year cloud-first, AI-enabled platform modernization strategies
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 platforms and engineering practices
Lead reusable intelligence components and foundational services supporting AI, analytics, automation, customer intelligence, predictive analytics, GenAI, agentic systems, and decisioning
Evaluate emerging AI and data technologies and establish adoption strategies
Own the servicing operational reporting ecosystem and drive self-service reporting, metric standardization, real-time intelligence, and reusable reporting frameworks
Build and lead a high-performing engineering organization through coaching, mentoring, succession planning, and technical leadership development
Establish engineering operating models, delivery practices, quality standards, and cross-functional partnerships

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
Proven experience leading enterprise-scale data platform engineering organizations, with end-to-end accountability for technology strategy, architecture, engineering execution, platform reliability, and operational excellence
Deep expertise in designing, building, and modernizing cloud-native data platforms, distributed systems, data lakes, and large-scale data ecosystems supporting mission-critical business capabilities
Demonstrated success defining and executing multi-year platform modernization and cloud transformation strategies, focused on simplification, standardization, scalability, resiliency, automation, and reuse
Strong experience with Data as a Service (DaaS), Metrics as a Service (MaaS), reusable data products, intelligence access layers, data ingestion platforms, and governed APIs
Deep knowledge of data ingestion and processing, data federation, metadata management, data quality, lineage, cataloging, master data management, and enterprise data lifecycle management
Strong 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
Demonstrated experience establishing AI-ready data foundations supporting advanced analytics, machine learning, Generative AI, customer intelligence, agentic systems, automation, and intelligent decisioning
Strong understanding of modern 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
Strong 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
Strong 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