Skills and Competencies - Working knowledge of Python, SQL, and Java for data pipeline development, ETL/ELT processes, and software service development
- Foundational knowledge of AWS cloud services, including Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, and Amazon RDS; experience with Microsoft Azure and SSIS is preferred
- Familiarity with relational database concepts, including tables, keys, joins, indexes, views, and normalization; knowledge of non-relational databases such as DynamoDB or MongoDB is preferred
- Foundational understanding of REST APIs and GraphQL APIs, including schemas, queries, mutations, and web service integration; experience with API testing tools such as Postman, Swagger, or OpenAPI is preferred
- Experience developing reports and dashboards using Tableau or Power BI is preferred
- Familiarity with Git and GitHub for source-code management, version control, and collaboration
- Strong analytical, problem-solving, communication, and collaboration skills with attention to detail and a commitment to data quality, accuracy, and technical integrity
- Basic understanding of artificial intelligence concepts, with curiosity and enthusiasm for learning how AI tools can be used to improve processes and drive efficiency. Interest in exploring AI systems and a willingness to develop awareness of responsible AI practices, including risk management and ethical use
Education - Bachelor's degree in Computer Science, Software Engineering, Data Engineering, Information Systems, or a related field; equivalent practical experience may be considered
- Approximately 0-2 years of experience in data engineering, software engineering, application development, database development, or a related discipline
Responsibilities Supports the development, integration, and maintenance of data pipelines, software services, cloud-based solutions, APIs, and reporting platforms, collaborating with engineers, architects, analysts, and business stakeholders to deliver reliable and scalable outcomes.
- Develop, maintain, and support data pipelines and ETL/ELT processes using Python, SQL, AWS, Azure, and SSIS
- Extract, transform, validate, and load data across multiple source and target systems, ensuring accuracy, consistency, and data quality
- Support cloud-based data engineering solutions using AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Redshift, Amazon RDS, and CloudWatch
- Develop and consume REST APIs and GraphQL APIs, including queries, mutations, schemas, resolvers, error handling, and integrations with downstream systems and external services
- Develop, integrate, test, and support software services using Java and Python, and participate in testing, code reviews, deployment, and production support activities
- Write and optimize SQL queries, stored procedures, views, and data transformation logic across relational and non-relational databases
- Develop and maintain reports and dashboards using Tableau and Power BI to support data-driven decision-making across the organization
- Document data flows, API specifications, transformation rules, technical processes, and operational procedures to support maintainability and knowledge sharing
- Use Git and GitHub for source-code management, version control, collaboration, and pull requests
- Use approved AI-assisted development tools, including GitHub Copilot and AI agents, in accordance with Moody's security, confidentiality, and responsible-use requirements
About the Team Our Data Engineering team is responsible for building and maintaining the data infrastructure, pipelines, APIs, and software services that power Moody's data platforms and analytics capabilities. We design and deliver scalable, cloud-based solutions that enable data-driven decision-making across the organization, supporting a wide range of internal and external stakeholders. Collaboration is at the core of how we work - engineers contribute across the full data and software engineering lifecycle, from development and integration through to deployment and production support, while helping shape reusable frameworks, integration standards, and responsible engineering practices. By joining our team, you will work alongside experienced data engineers, software engineers, and architects on meaningful and impactful initiatives, and be part of a culture that values continuous learning, technical excellence, and the thoughtful adoption of AI-assisted development tools.
For US-based roles only: the anticipated hiring base salary range for this position is $95,500.00 - $138,550.00, depending on factors such as experience, education, level, skills, and location. This range is based on a full-time position. In addition to base salary, this role is eligible for incentive compensation. Moody's also offers a competitive benefits package, including not but limited to medical, dental, vision, parental leave, paid time off, a 401(k) plan with employee and company contribution opportunities, life, disability, and accident insurance, a discounted employee stock purchase plan, and tuition reimbursement.
