Morningstar's Direct Advisory Suite needs to be enhanced to empower financial advisors by streamlining their workflows, including investment research, portfolio analysis, financial planning, and client reporting. The goal is to design, code, and deliver scalable, secure, and resilient systems for the future of financial advice.
Requirements
- Expert-level coding ability in one or more modern programming languages (e.g., Java, C-Sharp, Python, TypeScript/JavaScript).
- Deep expertise in cloud-native architectures (AWS preferred), microservices, APIs, containers, and event-driven systems.
- Hands-on experience with data-intensive and performance-sensitive applications.
- Strong knowledge of CI/CD pipelines, DevOps practices, monitoring, and infrastructure-as-code.
- Experience embedding security, privacy, and compliance (e.g., GDPR, CCPA) into applications.
- Extensive exposure to AI solutions is a must have.
- Experience in integrating with data providers, and expertise in Authentication and Authorization are desirable.
Responsibilities
- Design, implement, and ship critical features of Direct Advisory Suite that support advisor workflows such as research, portfolio analysis, proposal generation, and reporting.
- Write production-quality code across the stack, with a strong emphasis on reliability, scalability, and performance.
- Drive technical solutions from design through deployment, ensuring delivery timelines are met without compromising quality.
- Conduct design and code reviews, ensuring adherence to best practices, performance requirements, and security standards.
- Partner with QA and DevOps teams to build automated testing, deployment, and monitoring pipelines that ensure high system availability.
- Build and evolve cloud-native, microservices-based systems that integrate with shared platform services.
- Optimize data-intensive workflows by collaborating with data engineering teams on data modeling, pipelines, and query performance.
Other
- This role is based in our Chicago office and follows a hybrid schedule of at least 4 days onsite per week.
- Make pragmatic trade-offs between speed of delivery, technical debt, and long-term scalability.
- Serve as a role model of engineering excellence by consistently delivering high-quality software.
- Mentor engineers through code reviews, pair programming, and hands-on technical guidance.
- Work closely with product managers, UX designers, and other engineers to ensure technical solutions align with advisor needs and business goals.
