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.

Skills and Competencies

• 5-8 years of experience designing, building, and optimizing scalable data engineering solutions using Databricks, AWS Glue, and Unity Catalog
• Proven expertise in developing and maintaining batch and streaming ETL/ELT pipelines, including workflow orchestration with Apache Airflow
• Strong understanding of Data Lake and Medallion Architectures, distributed processing frameworks such as Apache Spark, and cloud-native data platforms
• Experience with SQL and NoSQL databases, data warehousing, data governance, metadata management, lineage tracking, and security controls
• Hands-on experience with AWS/Azure services, Git-based version control, Terraform, and CI/CD pipelines
• Demonstrated proficiency in AI-enabled productivity tools and emerging technologies that improve engineering efficiency and delivery outcomes.

Education

• Bachelor's, Master's, or PhD degree in Computer Science, Information Technology, or a related discipline

Responsibilities

• Design, build, and maintain scalable data pipelines that process structured and unstructured data from multiple sources
• Implement high-performance data solutions using Databricks, Spark, AWS Glue, and other cloud-native services
• Manage and optimize ETL workflows, ensuring reliability, scalability, and operational efficiency
• Develop and maintain secure Data Lake and Data Warehouse environments that support analytics and reporting needs
• Establish data governance, lineage, quality monitoring, and access-control frameworks
• Collaborate with business stakeholders, analysts, and data scientists to deliver data solutions aligned with business objectives.

About the Team
The Asset Management Technology team delivers innovative data, analytics, and AI capabilities supporting Structured Finance solutions. The team collaborates globally to build scalable platforms and high-quality data products that enable informed investment decisions across financial markets.

Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, sex, gender, age, religion or creed, national origin, ancestry, citizenship, marital or familial status, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, military or veteran status, or any other characteristic protected by law. Moody's also provides reasonable accommodation to qualified individuals with disabilities or based on a sincerely held religious belief in accordance with applicable laws.
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.
For more information on the Securities Trading Program, please refer to the Securities Trading Policy on Moody's Compliance Expo page

Please note: STP categories are assigned by the hiring teams and are subject to change over the course of an employee's tenure with Moody's.