Data Engineer

This job is with Moody's, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

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.

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.

Responsibilities

• Develop and expand our core data platform in MS Azure, Fabric building robust data infrastructure and scalable solutions.
• Enhance datasets and transformation toolsets on the MS Azure platform, leveraging distributed processing frameworks to modernize processes and expand the codebase
• Design and maintain ETL pipelines to ensure data is transformed, cleaned, and standardized for business use.
• Collaborate with cross-functional teams to deliver high-quality data solutions, contributing to both UI and backend development while translating UX/UI designs into functional interfaces.
• Develop scripts for building, deploying, and maintaining data systems, while utilizing tools for data exploration, analysis, and visualization throughout the project lifecycle.
• Utilize SQL and NoSQL databases for effective data management and support Agile practices with tools like Jira and GitHub.
• Contribute to technology standards and best practices in data warehousing and modeling, ensuring alignment with overall data strategy.
• Lead and motivate teams through periods of change, fostering a collaborative and innovative work environment.
  
  

Skills and Competencies

• 3-6 years of cloud-based data engineering experience, with expertise in Microsoft Azure and other cloud platforms.
• Proficient in SQL and experienced with NoSQL databases, message queues, and streaming platforms like Kafka.
• Strong knowledge of Python and big data processing using PySpark, along with experience in CI/CD pipelines (Jenkins, GitHub, Terraform).
• Familiar with machine learning libraries such as TensorFlow and Keras, and skilled in data visualization tools like Power BI/Fabric and Matplotlib.
• Expertise in data wrangling, including cleaning, preprocessing, and transformation, with a solid foundation in statistics and probability.
• Excellent communication skills for engaging with technical and non-technical audiences across all organizational levels.
• Experience in UI development, translating UX/UI designs into code, data warehousing concepts, API development and integration, and workflow orchestration tools is desired.
  
  

Education

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Mathematics, Statistics, or a related field
• Relevant certifications in data science and machine learning are a plus
  
  

About The Team

Our Technology Services Group (TSG) Team is responsible for delivering Innovative, data driven tech solutions. We build solutions that power analytics, enable machine learning, and provide critical insights across the organization. By joining our team, you will be part of exciting work in building scalable, next-generation data solutions that directly impact business strategy.

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.