Software Engineer - Full Stack and Data (React / Python)
Software Engineering
EUR 44,200-70,800 / year
Software Engineer - Full Stack and Data (React / Python)
Vilnius, Lithuania
- Posted
- 08/25/2026
- Job reference
- 14665
- Experience level
- Experienced Hire
- Job category
- Engineering & Technology
- Line of business
- Technology Services Group
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.
If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.
- 3 years of hands on experience building and supporting user interface based web applications using React, including internships or professionally delivered academic projects, required to take ownership of features in the applications the team operates today
- Working experience with Python for backend development, ideally using FastAPI or a similar framework such as Flask or Django, including building and consuming RESTful APIs, required to support and extend the services behind the team’s applications
- Solid command of Structured Query Language, including writing queries, joins, and aggregations against relational databases, required as the direct foundation for learning PySpark; a structured, mentored learning path into PySpark and data engineering is built into this role, so prior big data experience is preferred but not required
- Foundational software engineering discipline, including Git based version control, code reviews, testing, documentation, and Agile ways of working, with a willingness to grow into continuous integration and continuous delivery, secure coding, and cloud practices used across the team
- Strong analytical and problem solving skills, required to investigate application and data issues, learn quickly from feedback, and contribute effective solutions with support from senior engineers
- Clear communication and dependable collaboration, along with genuine curiosity and drive to grow into data engineering and AI enabled workloads, required to work effectively within the team, ask insightful questions, and take on increasing responsibility on highly visible enterprise initiatives
- Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use.
- Bachelor’s degree or higher in Computer Science, Information Technology, Software Engineering, or a related technical field
- Support, enhance, and help maintain the team’s React based web applications, resolving defects and delivering improvements that keep users productive from day one
- Develop and support FastAPI based backend services and RESTful APIs, with guidance from senior engineers, ensuring reliability and performance
- Take growing ownership of features end to end, from requirement clarification through deployment, enabling senior engineers to focus on platform and architecture work
- Write clean, maintainable, well tested code in React, Python, and Structured Query Language, while actively participating in code reviews and adopting the team’s engineering best practices
- Follow a structured learning path from Structured Query Language into PySpark, supported by mentoring, training resources, and dedicated learning time, with the goal of contributing to data engineering workloads within the first several months
- Progressively contribute to the team’s data pipelines and data workloads as PySpark skills develop, growing toward shared ownership of data engineering deliverables
- Assist in monitoring applications, services, and data workflows, troubleshooting issues and participating in root cause analysis to ensure reliability and performance
- Work closely with business, product, and technical teams to understand priorities, clarify requirements, and communicate progress clearly and effectively
- Follow data governance, security, and enterprise compliance standards, and maintain clear documentation for applications, services, and data workflows
- Maintain source code repositories and automated build and deployment pipelines using GitHub or Azure DevOps to support reliable and repeatable releases
Annual base salary gross: €44,200.00 to €70,800.00. Applicable to Lithuania candidates: The base salary range represents the low and high end of the Moody’s salary range for this position. Actual salaries will vary and will be based on various factors, such as candidate’s qualifications, skills, and competencies. The salary is one component of Moody’s total compensation package for employees. Other rewards and benefits include the following: Medical, Personal Accident, Life Insurance and Time Off.
Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.