Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 3+ years applied experience
Hands-on practical experience in system design, application development, testing, and operational stability
Hands-on experience in Java, React, Spring, Spring Boot, Oracle, Mongo, Postgress, Docker, Kubernetes, Cloud, MQueue, Kafka
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Overall knowledge of the Software Development Life Cycle
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Familiarity and exposure to AI technologies
Familiarity with modern front-end and backend technologies
Exposure to cloud technologies
