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Tier-1 brand, mid-level leadership role with broad tech stack and governance requirements.
Data engineering skills are transferable but finance-specific governance and responsible AI emphasize domain knowledge.
Explicit 5+ years and 2+ years leadership plus mandatory cloud, Big Data, and Java stack.
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Lead and mentor multiple software engineering teams with a focus on advancing financial technology solutions.
Accountable for technology and process implementations that impact resource allocation, coding governance, and operational efficiency across teams.
Drive adoption and scaling of AI-assisted engineering practices and SDLC automation to improve delivery speed, quality, and reliability across multiple teams.
5+ years applied software engineering experience with formal training or certification and at least 2 years leading technologists in complex domains.
Experience building automation-driven applications on AWS, hybrid, and on-prem platforms with expertise in CI/CD, performance, resiliency, and scalability.
Proficiency with Big Data and distributed cloud technologies including AWS Big Data services (Lambda, Glue, EMR, Spark), Kafka, and Java full stack development.
Experience in data management, data catalog, data governance, domain-driven design, microservices, event streaming, and building high-volume performant APIs.
Experienced leader capable of managing and influencing multiple cross-functional teams and senior stakeholders in a large enterprise environment.
Strong expertise in cloud-native big data platforms and modern software architecture including AI-assisted development tools integration.
Strategic thinker with ability to define governance and safe scaling patterns for responsible AI use in engineering workflows focused on security, compliance, and operational excellence.