QA Analyst: Data Reliability

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. 

Skills and Competencies.

• 3+ years of experience in data validation , data QA, analytics , or related reliability testing roles, with expertise in SQL for querying large-scale data (e.g., Databricks ).
• Proficiency in Python or PySpark for validation scripting or data analysis, and experience with Kafka and stream-processing systems.
• Familiarity with NoSQL databases like MongoDB and validation of REST APIs using tools such as Postman or Swagger.
• Solid understanding of data pipelines, ETL/ELT processes , and transformation workflows, with the ability to analyze and troubleshoot large datasets.
• Strong communication and documentation skills to support collaborative projects and reporting.
• Knowledge of data validation tools like Great Expectations or dbt tests , and experience integrating tests into CI/CD pipelines.
• Exposure to GenAI tools or development of agentic workflows for automation and decision support, as well as dashboard creation for data quality monitoring.

Education

• Undergraduate degree in Statistics, Computer Science or other quantitative/technology field required.

Responsibilities . 

• Validate data transformations across the pipeline-from Kafka event streams to processed data in Databricks and MongoDB, through APIs and UI. 
• Design and execute validation strategies that ensure data accuracy, completeness, and consistency. 
• Analyze large datasets to identify anomalies, data mismatches, and transformation issues. 
• Build, curate, and maintain test datasets to support multiple QA use cases and test environments. 
• Collaborate with developers and QA engineers to design test cases, validation rules, and data mapping documentation. 
• Develop scripts, dashboards, or alerts to proactively monitor data quality. 
• Participate in code reviews and provide input on schema design, transformation logic, and reliability strategies. 
• Document validation plans, data exception reports, and reliability metrics. 

About the team

We are seeking a highly analytical and detail-oriented Data Reliability Analyst to join our Software QA team. In this role, you’ll be responsible for ensuring the integrity, accuracy, and reliability of data flowing through our modern data pipeline-from ingestion through processing and visualization. This is a unique opportunity to work across systems including Kafka, Databricks, MongoDB, and REST APIs.

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.

For more information on the Securities Trading Program, please refer to the STP Quick Reference guide on ComplianceNet

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.