Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
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 experience across the SDLC, including system design, application development, testing, and operational stability.
Advanced Python experience (e.g., Pandas, NumPy) developing, debugging, and maintaining enterprise-scale codebases, with proficiency in SQL and database querying.
Hands-on experience with enterprise-authorized AI dev tools (coding/testing/troubleshooting/docs), with proven ability to validate and refine AI outputs for correctness, performance, and security.
Understanding of responsible AI in engineering (data sensitivity, secure input/output handling, resiliency/security), with the ability to guide peers on safe, effective team usage.
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Preferred qualifications, capabilities, and skills
Experience with front end technologies including React, Javascript, Typescript
Experience with data mesh technology and systems like Databricks is plus
Exposure to cloud technologies
Exposure to Banking/Finance or Risk domains
Possess good communication skills engage with stakeholders
