Senior Data Quality Engineer

About the Business: LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertically, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, https://risk.lexisnexis.com About our Team: This group is collaborative and supportive, with members committed to each other's growth. Successful teams here are quick learners who adapt, deliver value, and work well together. You will design automation strategies for critical applications and data infrastructure, support adoption of AI tools for engineering productivity, and help engineers build, monitor, and maintain high-quality products for clinical data use cases. About the Role: A senior Data QA & automation engineer is needed to direct quality assurance activities for the enterprise data lake platform. This position involves developing thorough testing protocols, possessing substantial knowledge in both general and data quality validation, and utilizing AI tools to enhance engineering effectiveness for the team. Responsibilities: Test Automation & Integration: architect and maintain end-to-end testing frameworks to support a variety of engineers working across various services (APIs, UI/UX, data pipelines, serverless applications). Testing Protocol Establishment: define and inform best practices on maintaining quality metrics across our data and application platforms. Data Quality and Validation: design and implement frameworks to help profile, monitor, proactively detect issues with critical data products. AI-leveraged Engineering: leverage LLMs to accelerate tasks like