Manager, Software Development & Engineering (Java Fullstack)

Key Responsibilities

• Build and deliver full-stack software capabilities for investment research initiatives, contributing hands-on to design, development, testing, and support. • Translate business needs into clear technical approaches by partnering with product owners, researchers, architects, and engineering peers. • Design and implement cloud-ready, event-driven services and integration patterns that improve scalability, reliability, and reuse across the broader platform. • Drive engineering excellence through clean code practices, automated testing, observability, and secure-by-design delivery. • Strengthen the team’s delivery model by improving CI/CD workflows and DevOps practices to increase quality and speed to production. • Diagnose and resolve complex production and integration issues using deep application and environment knowledge, while improving long-term resiliency. • Mentor and support fellow engineers through coaching, feedback, and inclusive collaboration. • Communicate priorities, tradeoffs, and progress with ownership and transparency to both technical and business partners. • Contribute to modernization efforts that improve user experience and align with evolving architecture standards. • Incorporate approved Generative AI capabilities to enhance developer productivity and code quality while following enterprise governance, security, and compliance expectations. ​

Required Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field, or equivalent practical experience. • 5+ years of experience developing production-grade applications using Java (Spring Boot) and Python. • Demonstrated ability to build cloud-ready, event-driven microservices and APIs at scale using common messaging patterns (e.g., Kafka, RabbitMQ) and RESTful services. • Proven experience designing and building hybrid on-premises and cloud integrations. • Strong working knowledge of SQL (e.g., PostgreSQL) and NoSQL technologies (e.g., MongoDB, DynamoDB, Bigtable), and sound judgment on when to apply each. • Ability to work with financial datasets and partner effectively on data engineering workflows and analytics use cases. • Interest in building data visualizations or dashboards using Python-based tooling (e.g., Plotly Dash or similar). • Hands-on experience using CI/CD and container-based delivery practices (e.g., GitHub CI/CD, Docker, Kubernetes, Bamboo/Jenkins). • Working knowledge of secure coding and code quality practices using common analysis tools (e.g., SonarQube, CodeQL , Veracode). • Demonstrated skill in designing maintainable solutions using established engineering standards (e.g., SOLID principles, 12-Factor App), appropriate data structures, algorithms, and modern design patterns.

Technical nice-to-haves