Senior Quality Test Engineer II
Would you like to be part of a team that delivers high-quality software to our customers?
Are you a visible champion with a ‘can do’ attitude and enthusiasm that inspires others?
About the Business
RELX is a global provider of information-based analytics and decision tools that help customers across industries make informed decisions, improve outcomes, and increase productivity. Serving customers in more than 180 countries, RELX employs thousands of professionals worldwide, including a large global technology community. LexisNexis Risk Solutions, part of RELX, provides data, analytics, technology, and workflow solutions that help organizations assess and manage risk, improve operational efficiency, and support compliance.
Inclusion & Accessibility Statement
RELX and LexisNexis Risk Solutions are committed to creating an inclusive workplace where everyone can thrive. We consider all qualified applicants regardless of race, ethnicity, color, religion, sex, gender identity or expression, sexual orientation, age, disability, veteran status, national origin, or any other protected characteristic. We are committed to providing reasonable accommodationsthroughout the recruitment process and employment lifecycle.
About the Team
You’lljoin a collaborative engineering teambuilding scalable, high-quality software solutions across backend, frontend, and cloud. The team works closely with cross-functional partners, values knowledge sharing and continuous learning, and encourages everyone to contribute ideas and improvements while balancing technical excellence with delivery.
About the Role
We are seeking a Senior Data Quality Assurance & Automation Engineer to help drive quality across our enterprise data lake platform. In this role, you will design and implement scalable testing and data quality frameworks, collaborate with cross-functional teams, and leverage automation and AI-assisted engineering practices to improve efficiency and reliability. We welcome candidates with diverse backgrounds and experiences who are passionate about quality engineering, data excellence, and continuous improvement.
Responsibilities:
Design and maintainautomated testing frameworks for APIs, applications, data pipelines, and cloud-based services.
Ensure data quality through data validation, profiling, reconciliation, monitoring, observability, and automated quality controls.
Establish and improve testing standards by defining quality metrics, best practices, and testing processes across platforms.
Leverage AI tools to improve engineering efficiency through test case generation, documentation, code reviews, and synthetic test data creation.
Build automation solutions including internal tools, CI/CD processes, dashboards, and workflows that improve reliability and scalability.
Apply modern engineering practices using Python, Node.js, SQL, APIs, microservices, distributed systems, and cloud platforms such as AWS, Azure, or GCP.
Work with modern data platforms including data lakes, data warehouses, Databricks, Spark, Kafka, Delta Lake, Looker, or similar technologies.
Collaborate with global teams and provide reasonable overlap with U.S. business hours. Experience in regulated industries and Infrastructure as Code tools (Terraform, CloudFormation) is a plus.
Requirements:
Experience in test automation, quality engineering, software testing, data quality, or related areas supporting complex applications and data platforms.
Strong automation experience, including CI/CD pipelines and tools such as Jenkins, GitLab CI, GitHub Actions, Airflow, or similar technologies.
Proficiencyin Python, Node.js, SQL, or similar programming languages.
Experience implementing data quality practices, including data validation, profiling, reconciliation, monitoring, and automated quality controls.
Understanding ofAPIs, microservices, backend systems, and modern software architecture principles.
Experience working with cloud platforms such as AWS, Azure, or GCP, and distributed systems.
Familiarity with data lakes, data warehouses, Databricks, Spark, Kafka, Delta Lake, Looker, or similar modern data technologies.
Experience with testing, monitoring, and observability tools such as Playwright, pytest, Jest, Great Expectations, Datadog, Prometheus, CloudWatch, or similar solutions, along with effective collaboration across global teams and overlap with U.S. business hours.
Learn more about the LexisNexis Risk team and how we work
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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