Sr. Data QA Engineer

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.

Education

• 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 shaping the reusable platforms, frameworks, and responsible AI practices the wider organization builds on.  

By joining the team, you will write the code behind those products, working alongside experienced engineers on some of the most interesting problems in applied AI, with the support, code review, and mentorship to keep growing — leveraging cutting-edge cloud technologies and machine learning frameworks to transform how Moody's delivers insight and value, responsibly and at scale.