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Tier-1 brand, metro location, mid-level generalist title, and broad skills increase candidate competition.
Core data engineering skills transfer across industries, but pricing and derivatives domain knowledge favors finance backgrounds.
Explicit 5+ years, 2+ years leadership, and mandatory tech stack and domain experience make filters strict.
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Lead modernization and re-engineering of pricing data processing and client-delivery platforms for Fixed Income and Derivative pricing, focusing on scalability, resilience, and security across on-prem and AWS cloud-native environments.
Maintain and enhance existing pricing data pipelines to improve reliability, performance, and supportability while optimizing end-to-end data flows and storage.
Drive adoption and governance of enterprise AI-assisted software engineering practices to improve code quality, delivery speed, and operational outcomes across teams, including setting validation standards and promoting automation reuse.
5+ years of applied software engineering experience with formal training or certification and at least 2 years leading technical teams in solving complex domain problems.
Strong hands-on Python development experience building and supporting production systems.
Solid understanding of relational SQL and NoSQL databases, data modeling, and data structures.
Experience designing hybrid architectures spanning on-premise and AWS cloud-native services.
Experienced in modernizing and optimizing complex data pipelines, ideally in financial services or related domains involving Fixed Income and derivatives pricing.
Skilled at leading teams in adoption and governance of AI-assisted engineering tools within secure, mission-critical environments.
Proficient in designing and deploying scalable cloud-native applications with a strong focus on software development lifecycle automation and security compliance.