Senior Software Engineer

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 as a data engineer with strong expertise in designing, implementing, and optimizing scalable data processing solutions using Data Bricks, Glue and Unity Catalog.
• Experience implementing data isolation strategies to protect sensitive information and managing access controls
• Proven track record in building and maintaining robust ETL/ELT data pipelines for both batch and streaming data. Hands-on ability to orchestrate and schedule ETL workflows through tools like Apache Airflow.
• Deep understanding of Data Lake architecture, including secure and scalable storage design on cloud platforms.
• Familiarity with Medallion Architecture principles for structuring data in bronze, silver, and gold layers to support analytics readiness.
• Solid experience with distributed data processing frameworks such as Apache Spark, including performance tuning and integration with big data platforms.
• Proficiency in writing complex queries and optimizing performance for both SQL and NoSQL databases.
• Knowledge of data governance frameworks, including compliance, metadata management, and data lineage tracking.
• Skilled in designing and optimizing data warehouse solutions for analytics and reporting purposes.
• Strong familiarity with the AWS/Azure cloud ecosystem and integration with various services for data engineering workflows.
• Experience with Git-based version control, Terraform for infrastructure as code, and CI/CD pipelines to support automated, repeatable deployment of data solutions.
• Competence in programming languages such as Python, Scala, or Java for data transformation and automation tasks.

• Exceptional problem-solving and analytical skills, with the ability to troubleshoot complex issues efficiently.
• Excellent communication and collaboration abilities, with a proven track record of effective teamwork.
• Familiarity with artificial intelligence coding assistants, such as Claude and GitHub Copilot to boost productivity and efficiency.

Education
Bachelor’s, Master’s, or PhD degree in Computer Science, Information Technology or related field is required.

Responsibilities

As the Senior Software Engineer within the Asset Management Technology teams, you will collaborate with global colleagues to develop and enhance our leading products in the Structured Finance area. In this role, you will play a key part in designing and implementing solutions that address complex challenges faced by clients in the fixed income finance sector.

• Work closely with business stakeholders, analysts, and data scientists to ensure data solutions meet analytical and operational needs.
• Take ownership of designing and maintaining scalable data pipelines that ingest, process, and store both structured and unstructured datasets.
• Utilize Data Bricks for high-performance data processing and integration with other cloud native services such as S3, Glue.
• Ensure optimal query performance and reliability when working with SQL and NoSQL databases.
• Manage ETL workflows using Apache Airflow, maintaining reliability and minimizing downtime.
• Architect and oversee Data Lake environments, ensuring proper organization, security, and accessibility.
• Implement data isolation and security measures to protect sensitive information in compliance with privacy regulations.
• Establish and maintain data governance practices, including metadata management, data lineage tracking, and quality monitoring.
• Develop and enhance data warehouse solutions to support reporting and business intelligence initiatives.
• Monitor, troubleshoot, and optimize data workflows to ensure smooth operations.