QA Engineer - Databricks

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- 6 years of experience in Software Quality Assurance or Data Quality Engineering within large-scale enterprise data platforms

Strong hands-on experience with Databricks SQL and Python, including testing of notebooks, workflows, and scheduled jobs

Solid understanding of Medallion architecture (Bronze, Silver, Gold) and data lifecycle validation practices

Expertise in PySpark for data validation, test automation, and building scalable testing frameworks

Strong proficiency in SQL and data validation techniques across dataset, record, schema, and transformation levels

Experience designing integration, end to end, and regression testing strategies with an automation first mindset

Experience working in Agile or Scrum environments with tools such as Xray for test management and Jira for defect tracking

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.

Education

Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related field

Responsibilities

Ensure data quality, reliability, and correctness across large scale Databricks batch pipelines through automated validation and testing practices.

Own end to end data quality validation for Databricks pipelines across Bronze, Silver, and Gold layers

Validate data completeness, accuracy, consistency, timeliness, and business rule correctness using Databricks SQL and Delta tables

Perform dataset, record, schema, and transformation level validations including source to target mapping and derived field checks

Design, develop, and maintain reusable and scalable data validation frameworks using PySpark and Python on Databricks

Automate integration, regression, and end to end testing for notebooks, workflows, and scheduled jobs

Define and implement test data management strategies including data refresh, masking, and environment isolation

Manage test cases, execution, and defect tracking using Xray and Jira while maintaining test documentation and validation evidence

Collaborate with engineering, platform, and product teams to enforce data quality standards and communicate risks and release readiness

About the Team

Our Data Platform and Engineering team is responsible for building and maintaining scalable, high quality data solutions that power critical business insights and analytics. By joining this team, you will collaborate with cross-functional experts across engineering, product, and platform functions to drive innovation in modern data architectures using Databricks and Delta Lake. The team is committed to adopting automation, advanced analytics, and responsible AI practices to ensure reliable and high performing data ecosystems.

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.