oracle
Director Software Engineering - Data Engineering, Metadata management, Generative AI, DaaS, MaaS
American Express
Chennai, IND
Full-time
Director · 10+ years experience
Hybrid
Discovered 2 weeks ago
Full Job Posting
Qualifications
- 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, with a focus on simplification, standardization, scalability, resiliency, automation, and reuse.
- Strong experience developing and operating enterprise data capabilities such as 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 modern data engineering principles and technologies, including 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, including standardized metrics and KPIs, self-service analytics, real-time intelligence, and reusable reporting frameworks.
- Demonstrated experience establishing AI-ready data foundations that enable 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 large language models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, semantic search, knowledge management, context engineering, and reusable AI/intelligence services.
- Proven ability to evaluate emerging data, cloud, AI, and GenAI technologies and establish enterprise adoption strategies that balance innovation with architecture standards, scalability, security, governance, and business priorities.
- Strong knowledge of enterprise data governance, security, privacy, risk, and regulatory requirements, with demonstrated experience embedding data quality, access controls, lineage, retention, auditability, and governance into platform architecture and engineering practices.
- Demonstrated ability to establish engineering standards and operating models that improve software quality, delivery velocity, platform availability, resiliency, performance, observability, and operational effectiveness.
- Proven ability to partner effectively across Product, Technology, Data Science, Enterprise Architecture, Information Security, Risk, Compliance, Operations, and business organizations to define strategic roadmaps and deliver enterprise capabilities.
- Strong business and technology acumen with the ability to translate complex data and engineering strategies into measurable customer, operational, and business outcomes.
- Exceptional communication and executive-influencing skills, with demonstrated ability to communicate complex technology strategies, architecture decisions, investment priorities, risks, and trade-offs to senior technical and business leaders.
- Proven people leadership experience, including building, developing, mentoring, and scaling high-performing engineering organizations; developing technical leaders; and supporting talent development and succession planning.
- Demonstrated ability to lead through influence across complex, matrixed organizations and drive adoption of common platforms, reusable capabilities, engineering standards, and enterprise technology strategies.
- Strong commitment to engineering excellence and continuous improvement, with demonstrated success fostering a culture of accountability, innovation, collaboration, customer focus, and operational excellence.
Responsibilities:-
- Proven experience leading enterprise-scale data platform engineering organizations, with end-to-end ownership of strategy, architecture, execution, and operational excellence.
- Deep expertise in designing, building, and modernizing cloud-native data platforms, distributed systems, and large-scale data ecosystems supporting mission-critical business operations.
- Demonstrated success delivering multi-year platform modernization and cloud transformation initiatives, driving simplification, standardization, scalability, resilience, and platform reuse.
- Experience establishing and operating Data as a Service (DaaS), Metrics as a Service (MaaS), reusable data products, intelligence access layers, and API/event-driven data platforms.
- Strong expertise in data engineering, metadata management, data quality, lineage, cataloging, governance, master data management, and enterprise data lifecycle management.
- Deep understanding of real-time data processing, event-driven architectures, streaming platforms, APIs, and operational reporting platforms that enable timely, trusted, and actionable business insights.
- Experience building AI-ready data foundations that support advanced analytics, machine learning, GenAI, customer intelligence, agentic systems, and intelligent decisioning through governed, contextualized, and discoverable data assets.
- Strong understanding of AI/ML ecosystems, including vector databases, Retrieval-Augmented Generation (RAG), semantic search, knowledge management, context engineering, and reusable AI platform services.
- Proven ability to embed security, privacy, risk management, compliance, and governance into data platform architecture and engineering practices while meeting enterprise and regulatory requirements.
- Demonstrated ability to partner with Product, Technology, Data Science, Enterprise Architecture, Operations, Risk, and Business leaders to define strategic roadmaps and deliver measurable business outcomes.
- Exceptional executive presence with a proven track record of influencing senior leadership, driving enterprise-wide platform adoption, and translating complex technical strategies into business value.
- Strong people leadership experience with success in building, mentoring, and scaling high-performing engineering organizations while fostering a culture of innovation, accountability, operational excellence, and continuous learning.
About American Express
Apply for this job in 1 click
Skip the repetitive application forms
Install the Base Career Chrome Extension and autofill job applications across major job boards with your profile.
Trusted by over 500,000 job seekers on Base Career
More from this employer
More jobs at American Express
Senior Analyst-Risk Management
Bengaluru, IND
Discovered TodayFull-time
Analyst-Compliance
Gurugram, IND
Discovered TodayFull-time
Sr Data Engineer - Financial Data Engineering
Phoenix, USA
Discovered TodayFull-time
Financial Analyst
Gurugram, IND
Discovered TodayFull-time
Manager-Business Development
, USA
Discovered TodayFull-time
Remote Travel & Concierge Experience Bilingual Agent
Québec, CAN
Discovered TodayFull-time
Associate-Digital Product Operations
Gurugram, IND
Discovered TodayFull-time
AI Engineer II
Gurugram, IND
Discovered TodayFull-time