Software Quality Engineer

Vizient•Irving, TX

42d

About The Position

In this role, you will specialize in analytics and have a critical role in ensuring the accuracy, integrity, and reliability of Vizient's data-driven products and insights. You will apply Agile and Software Development Lifecycle (SDLC) QA (Quality Assurance) methodologies to validate functional software components and the analytical outputs they generate. You will ensure that business intelligence dashboards, predictive models, and data pipelines meet quality standards and deliver trustworthy insights that support decision-making across the healthcare ecosystem.

Requirements

Relevant degree preferred. Degree in Computer Science, Data Analytics, or related field preferred.
2 or more years of experience in QA with a strong focus on data testing, analytics validation, and Business Intelligence/Extract, Transform, Load (BI/ETL) systems.
Proficiency in SQL/PL-SQL, writing complex queries, joins, and aggregations used in validating analytical outputs.
Experience with QA automation frameworks (Selenium, or similar) and Python for scripting, data validation, and automation.
Knowledge of Agile methodologies such as Scrum and Kanban.
Strong problem-solving and analytical skills, an ability to identify subtle inconsistencies in complex data.
Excellent communication skills, with experience presenting QA findings to both technical and business stakeholders.

Nice To Haves

Familiarity with Artificial Intelligence / Machine Learning (AI/ML) tools and methodologies is a plus
Exposure to BI/analytics tools such as Tableau, Power BI, or similar preferred.
Familiarity with validating data pipelines in cloud-based environments, Azure is preferred.
Understanding of statistical concepts, data modeling basics, their impact analytical outputs is a plus.

Responsibilities

Analyze requirements, data flows, and design specifications to create comprehensive test strategies that emphasize analytical accuracy and data validation.
Design, execute, and maintain test plans that cover data quality, transformation logic, aggregation rules, and business logic validation in addition to functional and regression testing.
Develop and maintain automated test scripts for data validation and analytical pipelines using tools such as Selenium, or Python-based frameworks.
Validate Extract, Transform, Load (ETL) processes, reporting layers, and dashboards; ensuring consistency of Key Performance Indicators (KPIs), metrics, and visualizations with underlying data sources.
Write complex SQL/PL-SQL queries to validate data integrity, and ensure analytical outputs are aligned with business requirements.
Partner with data engineers and business intelligence developers to verify model accuracy, statistical outputs, and integration of analytical components.
Support validation of AI/ML models by testing input/output integrity and ensuring model-driven insights are aligned with business logic.
Identify data anomalies, conduct root cause analysis, and recommend improvements in data collection, transformation, and presentation.
Track, manage, and prioritize defects related to data accuracy and analytics, collaborating with technical and business teams for resolution.
Provide recommendations to enhance data governance, reporting consistency, and analytical system scalability through QA best practices.
Contribute to the creation of regression suites for recurring analytics validation, ensuring accuracy across multiple releases