QA Automation Lead for Drug Discovery & Data Validation

Cognizant; Buenos Aires; Híbrido; ARS 1.800.000 - 3.200.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Wellbeing programs

Descripción de la vacante

Cognizant in Argentina is seeking an experienced QA Automation Test Lead to drive quality engineering, automation strategy, and risk-based testing across critical digital solutions supporting pharmaceutical early discovery research.

The successful candidate will collaborate with scientists, product owners, data engineers, and QA teams to ensure reliability, traceability, and integrity of data-driven scientific applications used throughout the drug discovery lifecycle, with a hybrid work model.

Formación

• Advanced English level.
• 10+ years of software testing, quality assurance, and quality engineering experience.
• Significant experience leading enterprise-level QA and test automation initiatives.
• Experience working directly with senior technical, scientific, product, and business stakeholders.

Responsabilidades

• Define and own the test automation strategy, framework roadmap, quality gates, test estimation models, and release readiness approach.
• Lead quality planning throughout discovery, design, development, testing, deployment, and production support phases.
• Develop and maintain automation frameworks, reusable libraries, and scalable testing solutions.
• Establish risk-based testing methodologies and quality governance standards.
• Mentor QA engineers and drive best practices in test automation and quality engineering.

Conocimientos

Test automation

Quality engineering leadership

Selenium

Playwright

Cypress

Robot Framework

Java

Python

SQL

Data validation

Azure DevOps

Git

Educación

Bachelor's degree in Computer Science or related field

Life sciences background

Herramientas

Jenkins

GitHub Actions

Azure DevOps Pipelines

Jira

HP ALM

Descripción del empleo

Cognizant in Argentina is seeking an experienced QA Automation Test Lead to drive quality engineering, automation strategy, and risk-based testing across critical digital solutions supporting pharmaceutical early discovery research.

The successful candidate will collaborate with scientists, product owners, data engineers, and QA teams to ensure reliability, traceability, and integrity of data-driven scientific applications used throughout the drug discovery lifecycle, with a hybrid work model.