QA Automation Test Lead

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

• Data visualization
• In Vivo Research

We are 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.

This role will work closely with scientists, product owners, data engineers, business analysts, UX teams, and development teams to ensure the reliability, usability, traceability, and integrity of scientific applications used throughout the drug discovery lifecycle.

The ideal candidate brings deep expertise in test automation, quality engineering leadership, scientific workflow validation, data-intensive applications, and pharmaceutical research environments.

Key Responsibilities

• 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.

Test Design & Execution

• Translate business requirements, scientific workflows, user stories, acceptance criteria, and interface specifications into comprehensive test scenarios and detailed test cases.
• Design, develop, and execute automated tests covering:
  • UI Testing
  • API Testing
  • Integration Testing
  • Regression Testing
  • Data Validation Testing
  • Smoke Testing
  • End-to-End Testing
• Perform exploratory and usability testing to validate researcher-centric workflows.
• Ensure comprehensive validation of business-critical scientific applications.

Scientific Workflow Validation

• Experiment and study setup
• Sample and compound management
• Assay workflows
• Results review and analysis
• Scientific calculations
• Data visualization
• Search and reporting
• Collaboration capabilities
• Data export and sharing

Data Quality & Integration Validation

• Verify data completeness, lineage, transformations, calculations, metadata, identifiers, and reconciliation across systems.
• Validate complex integrations between scientific platforms and enterprise applications.
• Conduct source-to-target data verification using SQL and automated validation approaches.
• Ensure traceability and integrity of research data throughout the application landscape.

Defect & Release Management

• Manage defect lifecycle activities including logging, triage, prioritization, retesting, closure, and trend analysis.
• Facilitate defect review meetings, root cause investigations, and quality risk assessments.
• Provide quality dashboards, test execution metrics, and release recommendations.
• Coordinate production smoke testing and post-release validation activities.

CI/CD & Test Automation Integration

• Integrate automated testing into CI/CD pipelines.
• Support release management through automated execution suites.
• Drive continuous testing practices across distributed delivery teams.
• Optimize automation execution, reporting, and deployment readiness.

The Successful Candidate Will Validate Applications Supporting

• Target Identification & Validation
• Hit Identification
• Hit-to-Lead Research
• Lead Optimization
• Assay Development
• Compound Management
• In Vitro Research
• In Vivo Research
• Translational Science

You Will Work With Solutions Used By

• Medicinal Chemistry
• Computational Chemistry
• Biology Research
• DMPK Teams
• Toxicology Teams
• Bioinformatics Teams
• Screening Operations
• Laboratory Operations
• Sample Management Groups

Required Qualifications

• Advanced English level,
• 10+ years of software testing, quality assurance, and quality engineering experience.
• Significant experience leading enterprise-level QA and test automation initiatives.
• Proven track record supporting complex, business-critical systems and cross-functional delivery teams.
• Experience working directly with senior technical, scientific, product, and business stakeholders.

Test Automation Expertise

• Selenium
• Playwright
• Cypress
• Robot Framework
• Java
• Python
• JavaScript
• TypeScript

API & Integration Testing

• REST APIs
• JSON payload validation
• Contract testing
• Authentication and authorization testing
• Service integration validation

Data Validation

• SQL
• Data quality testing
• Source-to-target reconciliation
• Data transformation validation
• Metadata verification
• Scientific data integrity testing

DevOps & Tooling

• Git-based source control
• Jenkins
• GitHub Actions
• Azure DevOps Pipelines
• Jira
• Azure DevOps
• HP ALM
• Test reporting tools

Preferred Qualifications

• Experience within pharmaceutical, biotech, CRO, laboratory informatics, or scientific research environments.
• Exposure to:
  • ELN (Electronic Laboratory Notebook)
  • LIMS
  • SDMS
  • CDS
  • Compound Registration Platforms
  • Screening Platforms
  • Bioinformatics Platforms
  • Research Analytics Solutions
• Understanding of:
  • Drug Discovery Processes
  • Chemistry and Biology Workflows
  • Scientific Metadata Management
  • FAIR Data Principles
  • Data Lineage and Governance
  • Controlled Vocabularies and Ontologies
• Familiarity with:
  • GxP environments
  • Computer System Validation (CSV)
  • Data Integrity Principles
  • Audit Trails
  • Electronic Records
  • Privacy and Compliance Standards

Education

Bachelor's or Master's degree in one of the following disciplines:

• Computer Science
• Information Technology
• Engineering
• Life Sciences
• Pharmacy
• Chemistry
• Biology
• Bioinformatics
• Related Technical or Scientific Fields

Work Model

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3 days a week in a client or Cognizant office in Tucuman, Buenos Aires. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.

Why Join Us?

This is a unique opportunity to lead quality engineering initiatives at the intersection of technology, automation, scientific innovation, and pharmaceutical research, helping accelerate the delivery of solutions that support the next generation of drug discovery and translational science.