Moody's Analytics is a global leader in ratings and integrated risk assessment, transforming how the world sees risk. The Software Engineer will contribute to ongoing feature development of web applications, collaborate with cross-functional teams, and assist in designing and developing new projects based on evolving business needs.
Responsibilities:
- Contribute to ongoing feature development of web applications based on service-oriented architecture, involving UI, Services and databases
- Work with the application development team leads on the technical and architectural direction of projects
- Research, analyze, design, and deliver solutions that are appropriate for business and application development strategies
- Participate in design, development and implementation of systems engineering activities, systems programming, and data center capabilities
- Work with cross-functional, globally dispersed development teams to support development efforts to meet business requirements
- Assist in designing and developing new projects and enhancements based on evolving business needs
- Interact with internal users to define system requirements and/or necessary modifications
- Complete documentation and procedures for installation and maintenance of software
- Design and implement ETL/ELT processes
- Build and maintain data lakes and warehouses
- Ensure data quality, governance, and security
- Collaborate with data scientists and analysts
- Mentor junior engineers and promote best practices
Requirements:
- Requires a Master's degree or foreign equivalent in Computer Science, Information Technology, or a related technical field plus one (1) year of experience as a Software Engineer or related position performing software development and designing technical solutions
- Must have experience with the following: with Python, SQL; cloud platforms including AWS, technical support, including troubleshooting, analyzing, and resolving defects in production, and QA environments; data modeling and pipeline optimization; building ETL pipeline using Microsoft SQL server; and Database migration from nonprod to production environment