Lead Software Engineer - Python/ Data

Overview In this role you lead software delivery within Corporate Technology’s Financial Planning & Analysis team, building secure, scalable products that support the firm’s objectives. You will act as a core technical contributor across multiple domains, driving AI-assisted engineering practices and ensuring high-quality, production-ready solutions. You collaborate closely with cross-functional partners to improve automation, stability, and architectural outcomes. This opportunity offers impact at scale within a trusted, market-leading financial technology environment. Compensation / Benefitscomprehensive health care coverageretirement savings planbackup childcaretuition reimbursementmental health supportfinancial coaching ResponsibilitiesDesign and implement creative software solutions and troubleshoot complex technical problemsDevelop secure, production-grade code and review peers' workLead adoption of AI-assisted engineering practices to improve code quality and delivery speed while standardizing validationLeverage the SDLC toolchain and automation capabilities to maximize value from automationAutomate recurring issues to boost operational stability of applications and systemsLead evaluation sessions with external vendors, startups, and internal teams on architecture and applicabilityOwn and drive secure coding, testing strategies, and incident/root-cause analysis supportcoach engineers on safe, compliant AI adoption within delivery practices Key requirementsSoftware engineering training or certification with 5+ years of applied experience (NAMR/APAC; India; LATAM; Hong Kong) or advanced applied experience (EMEA; LATAM-Brazil); Singapore per local guidanceHands-on experience delivering system design, application development, testing, and operational stabilityProficiency in Java, Python, or ScalaStrong AWS platform knowledge, core services, architecture best practices, and securityExtensive experience with big data technologies, particularly Apache SparkExperience leading the use of AI-assisted development tools with emphasis on validation for correctness, performance, and securityUnderstanding of responsible AI in engineering workflows and data handling for resiliency and securityProficiency across the Software Development Life Cycle and agile practices including CI/CD, resiliency, and securityPractical cloud-native experienceleadership and coachingcollaboration across cross-functional teamsproblem-solving and analytical thinkingJavaPythonScala