Associate 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

• 3-5 years of hands-on experience developing data pipelines using Python and PySpark, required to build and maintain large-scale extract, transform, and load workloads
• Strong working proficiency with Databricks, including notebooks, workflows/jobs, Delta Lake, and Unity Catalog, required to deliver production data pipelines on a modern lakehouse platform
• Advanced Structured Query Language skills, including complex joins, window functions, common table expressions, and query performance tuning, required to transform and curate data from relational and analytical sources
• Solid understanding of data warehousing concepts, dimensional modeling, and extract-transform-load and extract-load-transform best practices, required to design scalable, reliable, and maintainable data products
• Practical experience with at least one major cloud platform (Amazon Web Services, Microsoft Azure, or Google Cloud Platform), including cloud storage, compute, and orchestration services, required to deploy and operate pipelines in cloud environments
• Working knowledge of version control using Git, continuous integration and continuous deployment pipelines, and agile delivery practices, required to collaborate effectively within a distributed engineering team
• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using artificial intelligence tools to streamline workflows and enhance operational efficiency; proven ability to implement artificial intelligence-powered solutions to solve business challenges; demonstrates a growing awareness of artificial intelligence risk management and a commitment to responsible and ethical artificial intelligence use
• Strong analytical, problem-solving, and written and verbal communication skills, required to translate business requirements into technical solutions; prior experience with financial services, credit, or risk data is preferred

Education

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related quantitative field is required; equivalent professional experience will be considered
• Relevant certifications in Databricks, cloud data engineering, or data analytics are desired

Responsibilities

Design, build, and maintain Python and PySpark data pipelines on Databricks to deliver trusted, high-quality data to analytics and business teams.

• Designs, develops, and maintains scalable extract, transform, and load pipelines using Python, PySpark, and Databricks to ingest, cleanse, and integrate data from a variety of internal and external source systems 
  
• Writes, reviews, and tunes complex Structured Query Language queries and transformations to support reporting, analytics, and downstream data consumption 
  
• Implements data quality checks, monitoring, logging, and alerting across pipelines to ensure the accuracy, completeness, and timeliness of data products 
  
• Partners with data engineers, analysts, product owners, and business stakeholders to gather requirements and translate them into technical specifications and working data solutions 
  
• Troubleshoots and resolves production incidents, performs root-cause analysis, and applies performance improvements to existing pipelines, queries, and jobs 
  
• Participates in code reviews, contributes to shared coding standards, and produces clear documentation for pipelines, data models, and operational runbooks 
  
• Supports release activities through version control, continuous integration and continuous deployment pipelines, and agile ceremonies, working independently on assigned tasks while escalating complex issues to senior engineers 
  

About the team
Our Data Engineering team is responsible for building and operating the cloud data platform that powers analytics, reporting, and decision-making across the organization. We partner with business lines to deliver trusted data products, enable self-service analytics, and modernize our data infrastructure on the lakehouse.

By joining our team, you will be part of exciting work in cloud-based data engineering, large-scale data processing, and analytics enablement. You will also contribute to how we evaluate, adopt, and integrate artificial intelligence into our data products and engineering workflows, helping to accelerate delivery, improve data quality, and unlock new insights for our internal customers in a responsible and well-governed way.

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.