Senior Software Engineer at Morningstar
Act as a leading contributor in the architecture and development of software applications, machine learning applications, and other data products (30%). Research and develop applications that automate the current data collections process leveraging Machine Learning model creation and AutoML with cloud platforms (20%). Find creative solutions to complex development problems using cloud technologies (10%). Perform DevOps roles such as infrastructure management and develop areas of continuous and automated deployment (10%). Design for the big picture, including product roadmap over next quarter and years (10%). Remediate production issues and vulnerabilities timely thereby building instrumentation and operational readiness into the systems architecture (5%). Lead end-to-end design (5%). Support and improve critical products and legacy systems (5%). Act as a software guardian (5%).
- Master’s degree in Computer Science, Computer Engineering or a related field and 3 years of relevant software engineering experience.
- In the alternative, we will accept a Bachelor’s degree in Computer Science, Computer Engineering, or related field and 5 years of relevant software engineering experience.
- 3 years of experience in frontend and backend development utilizing DevOps.
- 3 years of experience building and maintaining professional software.
- 3 years of experience with backend XML, relational, and file-based databases (SQL or Postgres).
- 3 years of experience in software engineering best practices including Sonar approved coding standards, Test Driven development (TDD), Version control (Git), Code deployments (CI/CD: Jenkins, uDeploy), and monitoring performance using New Relic and Splunk.
- 2 years of experience building backend applications using Java and C#.
- 2 years of experience in scripting languages, including Python and NodeJS.
- 1 year of experience in Machine Learning Predictive analysis and model development in Python, data mining and extraction, and Auto ML.
- 1 year of experience working in Auto ML with cloud providers like Google Cloud Provider (GCP).
- 1 year of experience working with DevOps and infrastructure management through Amazon Web Services.