Sr. Data QA 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 Expertise in Python and Structured Query Language, including Snowflake, PostgreSQL, and Databricks, for data testing and quality assurance Proficiency in dbt to create data models, understand data transformations, implement data tests, and identify data quality issues Strong knowledge of Amazon Web Services, including Amazon S3, Amazon DynamoDB, AWS Glue, and AWS Lambda Strong knowledge of continuous integration and continuous delivery pipelines, DevOps practices, test automation tools, and testing frameworks Familiarity with Apache Airflow for understanding data extraction, transformation, and loading workflows, as well as version control tools such as Git Excellent decision-making, problem-solving, communication, and presentation skills, with the ability to translate complex requirements into effective quality assurance solutions Ability to influence change, coordinate solutions across teams, and provide guidance on quality assurance standards and best practices Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use.

Bachelor’s degree in Computer Science, Engineering, or a related discipline, or equivalent professional experience Responsibilities Lead data quality engineering practices that ensure reliable data and scalable testing across Moody’s products and platforms. Ensure data is reliable, accurate, and fit for use by data consumers Lead the design and implementation of comprehensive data test strategies and plans Develop and maintain automated test frameworks using dbt and Python data quality libraries Conduct code reviews and provide actionable feedback to strengthen data quality Debug data quality issues, identify root causes, and recommend effective solutions to data engineers Drive the adoption of quality assurance standards, best practices, and continuous process improvement Serve as a subject matter expert on assigned projects involving financial information Promote consistent data quality practices and coordinate solutions across engineering and product teams About the Team Our Digital Content and Innovation (DC&I) team is responsible for building and deploying intelligent, AI-powered solutions that drive innovation across Moody's products and platforms. We contribute to the organization by accelerating the development of next-generation analytical tools, enabling smarter client experiences, and advancing Moody's leadership in applied artificial intelligence.  The group brings together engineers, data scientists, and AI specialists who work across the full AI lifecycle, from experimentation and prototyping through to large-scale production deployment, while