Design and build cloud-native microservices, REST APIs, and highly available backend services supporting large-scale data requests. Translate business requirements into scalable platform solutions, contribute to architecture modernization, and uphold engineering practices including testing, observability, CI/CD, and code reviews. Troubleshoot production issues, improve reliability, and evaluate emerging data engineering and generative AI technologies. Mentor colleagues and collaborate across technical and business teams.
The ideal candidate is passionate about software craftsmanship, cloud technologies, and solving complex technical challenges. You enjoy working in a collaborative environment where innovation, continuous learning, and ownership are highly valued. You are comfortable navigating ambiguity, driving solutions from concept to production, and mentoring others while helping establish engineering excellence across the organization.
By joining Morningstar, you will have the opportunity to work on cutting-edge technologies, contribute to products that impact global investors, and help build a platform that serves as the foundation for Morningstar's future data delivery strategy.
Responsibilities
- Design and implement cloud-native microservices and APIs that support millions of data requests while maintaining high availability and performance. Participate in architectural design and contribute to long-term platform modernization initiatives.
- Partners with cross-functional stakeholders to translate business requirements into scalable technical solutions in data platform.
- Champion engineering best practices including test driven development, observability, code reviews, CI/CD, and operational excellence.
- Troubleshoot and resolve urgent production issues while continuously improving system reliability and resilience.
- Evaluate and adopt emerging technologies including new data engineering solutions and Generative AI to improve platform capabilities and developer productivity.
Qualifications
- Bachelor's degree in Computer Science, Software Engineering, or a related technical field.
- 5+ years of professional software engineering experience building enterprise-scale applications and distributed systems.
- Strong programming experience with Java and Spring Boot; additional experience with Python is a plus.
- Deep understanding of object-oriented design principles, design patterns, domain-driven design, and modern software architecture.
- Hands-on experience building and deploying cloud-native solutions on AWS with services such as ECS, Lambda, S3, SNS, SQS, CloudWatch, and IAM.
- Strong knowledge of databases including SQL Server, Redis, MongoDB, and data modeling best practices.
- Experience developing RESTful APIs and highly available, scalable backend services.
- Familiarity with CI/CD pipelines, automated testing, infrastructure-as-code, and DevOps practices.
- Strong communication skills and the ability to collaborate effectively across technical and business teams.
- Experience with financial services, investment data, market data platforms, or fintech environments is a plus.
Base Salary Compensation Range$90,489.00-$132,711.00
Incentive Target Percentage
12.5% AnnualMorningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
001_MstarInc Morningstar Inc. Legal EntitySimilar Jobs at Morningstar
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
Build and operate applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, MCP tools, APIs, and governed content-serving layers. The role emphasizes production reliability, provenance, security, cost and latency management, regression detection, and human-reviewed AI outputs. Responsibilities include cloud deployment, structured content modeling, telemetry, governance, mentoring, and collaboration on AI standards. Strong Python, TypeScript, AWS, API, data pipeline, and production LLM experience are required.
Top Skills:
Amazon BedrockAWSAzure Ai/Cognitive ServicesDockerFastapiGraphQLHeadless CmsInfrastructure As CodeLitellmLlmsMcpNode.jsPythonRagRestStructured OutputsTool/Function CallingTypescript
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
Build and operate production applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, APIs, MCP tools, and governed content-serving layers. Develop reliable extraction and classification agents, model evaluation harnesses, telemetry, and structured data pipelines. Ensure security, privacy, provenance, reliability, latency, and cost controls while mentoring engineers and contributing to AI governance and standards.
Top Skills:
Amazon BedrockAWSAzure Ai/Cognitive ServicesFastapiGraphQLLitellmLlmsMcpNode.jsPythonRagRestTypescript
Artificial Intelligence • Big Data • Enterprise Web • Fintech • Software • Financial Services
Build and operate production AI applications and shared platform capabilities using AWS Bedrock and Python. Develop AI agents, MCP servers, APIs, distributed services, retrieval architectures, orchestration frameworks, and evaluation systems. Partner with technical and business stakeholders to identify AI opportunities, modernize existing applications, and integrate AI into enterprise workflows. Influence architecture and engineering standards while supporting delivery planning and mentoring less experienced engineers.
Top Skills:
APIsAWSAws BedrockDistributed ServicesMcp ServersModel EvaluationObservabilityOrchestration FrameworksPythonRetrieval-Based Architectures
What you need to know about the Vancouver Tech Scene
Raincouver, Vancity, The Big Smoke — Vancouver is known by many names, and in recent years, it has gained a reputation as a growing hub for both tech and sustainability. Renowned for its natural beauty, the city has become a magnet for professionals eager to create environmental solutions, and with an emphasis on clean technology, renewable energy and environmental innovation, it's attracted companies across various industries, all working toward a shared goal: advancing clean technology.
