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Senior, niche big-data platform role at a Tier-1 bank reduces applicant density.
Strong data-platform skills are transferable, but enterprise governance and finance context raise fit sensitivity.
Explicit 10+ years, dual-language expertise, big-data, cloud, and platform leadership requirements make filters stringent.
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Design, develop, and operate scalable data platform components including ingestion, processing, storage, and access layers to support analytics, ML, and applications.
Provide technical guidance and direction across teams, influence data platform architecture and software development life cycle practices, including AI-assisted engineering tools adoption.
Lead team adoption of enterprise-authorized AI-assisted SDLC automation to improve delivery speed, quality, and operational outcomes while ensuring secure and compliant usage.
10+ years of applied software engineering experience, including system design, application development, testing, and operational stability for data platforms and backend systems.
Advanced proficiency in both Python and Java programming languages with backend engineering experience (APIs, services, distributed systems).
Hands-on experience with big data technologies such as Spark, Databricks, Data Lake, and building large-scale data pipelines.
Experience designing and operating data platform components in AWS cloud environments (ECS, EKS, EMR, Lambda).
Experienced in backend and data platform engineering within large, distributed corporate environments, comfortable collaborating across global, cross-time-zone teams.
Strong capability in leading adoption and governance of AI-assisted development tools and responsible AI usage in engineering workflows.
Deep expertise in distributed data processing, cloud infrastructure, and software delivery automation aiming to improve operational stability and delivery velocity.