Job Summary
Sr Quality Engineer with three to five years experience will design and execute robust automation and quality strategies for cloud native microservice applications using GCP AWS Azure Kafka Docker Gitlab and Karate frameworks while ensuring stable performant and secure releases for a global high technology client in a flexible hybrid work environment
Responsibilities
- Drive end to end quality assurance for microservice based applications by designing effective test strategies that ensure reliable customer facing solutions
- Develop and maintain robust automated test suites using Karate and JavaScript to validate application functionality performance and regression scenarios across services
- Implement cloud aware test approaches for GCP AWS and Azure environments to validate scalability resilience and integration of distributed components
- Configure and manage Docker based test environments to enable consistent reproducible and isolated execution of automated and exploratory test cycles
- Integrate automated tests into Gitlab continuous integration pipelines to enable fast feedback cycles and reduce defects reaching later stages of delivery
- Design and execute Kafka focused testing scenarios that validate message flows event ordering error handling and data integrity across asynchronous systems
- Collaborate closely with developers product analysts and site reliability teams to clarify requirements align quality goals and resolve defects efficiently
- Analyze test results defect trends and production incidents to identify quality risks propose improvements and strengthen overall engineering practices
- Create detailed yet clear test plans test cases and execution reports that provide transparent visibility into release readiness for business and engineering partners
- Apply secure coding and testing practices across cloud microservice and integration layers to minimize vulnerabilities and support resilient enterprise solutions
- Perform root cause analysis for critical defects and partner with engineering teams to implement corrective actions that prevent issue recurrence and improve system stability
- Optimize test coverage by prioritizing high value scenarios based on risk business impact and usage patterns ensuring efficient use of testing effort
- Mentor peers on automation best practices cloud testing patterns and quality mindset to uplift overall team capability while contributing reusable testing assets
Qualifications
- possess a degree in computer science engineering or a related field or equivalent practical experience with a strong focus on software quality and automation practices
- demonstrate hands on experience building and maintaining automated tests using Karate and JavaScript for api web and microservice validation
- bring proven experience testing applications deployed on GCP AWS and Azure with familiarity in using cloud services logs and monitoring tools during validation
- show solid understanding of Kafka concepts including topics partitions consumers and producers with practical experience validating event driven workflows
- exhibit proficiency with Docker containerization for creating reproducible test environments and running automated suites in isolated contexts
- apply practical experience with Gitlab or similar tools for continuous integration continuous delivery and version control driven quality workflows
- display strong understanding of microservices architectures including service contracts api gateways and dependency management from a testing perspective
- appreciate prior exposure to high technology domain products or platforms where reliability scalability and performance are critical success factors
- communicate clearly in cross functional teams by explaining defects test results and quality risks in a concise and solution oriented manner
- adapt effectively to hybrid work arrangements by collaborating virtually and onsite while maintaining consistent productivity and engagement
À propos de Cognizant
Cognizant (NASDAQ : CTSH) est un AI Builder et une entreprise de services numériques (ESN) élaborant des solutions complètes d’IA maximisant les investissements pour des résultats concrets. Sa profonde expertise des métiers, des processus et des technologies lui permet d’intégrer dans les systèmes technologiques le contexte unique de chaque organisation de l’ingénierie à la production à l’échelle. Son objectif : améliorer l’efficacité des équipes, créer de la valeur et permettre aux grandes entreprises de rester performantes dans un monde qui évolue rapidement. Pour en savoir plus : cognizant.ai ou @cognizant.
Renseignments suppplémentaires sur l'emploi
Les informations relatives à la rémunération du poste à pourvoir dépendent de la date de publication de l’offre de poste. Cognizant se réserve le droit de modifier ces informations à tout moment, sous réserve des lois applicables.
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