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Tier-1 brand, mid-level generalist title, metro location, and broad skillset raise candidate competition.
Requires financial-services data governance, regulatory knowledge and domain-specific tooling, limiting cross-industry transferability.
Explicit 5+ years plus mandatory data governance, APIs, Kafka and certification requirements tighten shortlisting.
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Lead planning and delivery of product data to support strategic business objectives, operations, analytics, and reporting within Post Trade Technology.
Drive adoption and governance of AI-assisted engineering practices to improve software quality, delivery speed, and operational outcomes in the SDLC toolchain.
Manage data risk identification, monitoring, and mitigation per firmwide policies while coordinating data accuracy, completeness, and timeliness requirements across stakeholders.
5+ years of applied software engineering experience with formal training or certification in software engineering concepts.
Experience in data technology, including data governance and data management.
Demonstrated expertise with AI-assisted software development tools and setting validation standards for correctness, performance, and security.
Strong knowledge of API lifecycle and documentation (OpenAPI/Swagger, REST, GraphQL), event-driven architectures or messaging platforms (e.g., Apache Kafka), and data privacy, security, and regulatory requirements in financial services.
Experienced in integrating data governance and AI-assisted development tools at enterprise scale within regulated financial services.
Capable of managing cross-functional collaborations between product, technology, analytics, and risk teams to ensure data quality and compliance.
Strong operational focus on delivering measurable improvements in software delivery, data risk management, and compliance through structured governance and automation.