Role will be part of our Quality Engineering & Assurance (QE&A) Practice. With more than 650 clients across industry verticals and a global footprint, Cognizant QE&A practice is a recognized thought leader in quality engineer and Assurance .As enterprises simplify, modernize and secure their legacy environments for the digital era, robust quality Engineering and assurance is essential. Quality takes an end-to-end connotation and must straddle both legacy and digital systems. Cognizant QE&A is reimagining QE&A, employing an end-to-end ecosystem approach with intelligent and automated QA processes. In so doing, increasing quality and speed to promote faster business and technology change, as well as a better customer experience.
Key Responsibilities
- Supporting end-to-end TDM solutions at enterprise scale, along with working knowledge of data protection regulations such as GDPR and DPA to ensure compliant handling of test data in lower environments.
- Database Expertise - Mainframe Db2, Oracle, SQL — including writing complex queries, understanding schemas, and working across relational and mainframe data structures.
- Working with Delphix platform for data virtualization, provisioning, and refresh operations across non-production environments.
- Performing data profiling to identify sensitive/PII data, and implementing data masking strategies to ensure compliance with data privacy and security standards.
- Design and manage virtual data copies, automate data refresh cycles, and reduce environment provisioning time using virtualization techniques.
- Creating synthetic test data to support testing needs where masked production data isn't sufficient or available, ensuring referential integrity and realistic data patterns.
- Integrating test data provisioning into CI/CD pipelines (e.g., Jenkins, GitLab CI, or similar), supporting automated test data readiness for continuous testing
- Work closely with QA, development, DBAs, and data governance teams to align test data strategies with compliance requirements. Ability to document TDM processes, standards, and contribute to building repeatable, scalable test data provisioning pipelines
Key Skills and Experience :
- Test Data Management: Experience supporting end-to-end TDM solutions at enterprise scale, along with working knowledge of data protection regulations such as GDPR and DPA to ensure compliant handling of test data in lower environments.
- Database Expertise: Strong hands-on experience with Mainframe Db2, Oracle, SQL — including writing complex queries, understanding schemas, and working across relational and mainframe data structures.
- TDM Platform Proficiency: Mandatory hands-on experience with the Delphix platform for data virtualization, provisioning, and refresh operations across non-production environments.
- Data Masking & Profiling: Proven experience performing data profiling to identify sensitive/PII data, and implementing data masking strategies to ensure compliance with data privacy and security standards.
- Data Virtualization & Refresh: Ability to design and manage virtual data copies, automate data refresh cycles, and reduce environment provisioning time using virtualization techniques.
- Synthetic Data Generation: Experience creating synthetic test data to support testing needs where masked production data isn't sufficient or available, ensuring referential integrity and realistic data patterns.
- CI/CD & Automation Integration: Understanding of integrating test data provisioning into CI/CD pipelines (e.g., Jenkins, GitLab CI, or similar), supporting automated test data readiness for continuous testing.
- Additional TDM Tool Exposure: Working knowledge of other TDM tools such as Broadcom TDM, IBM Optim, K2View, or GenRocket is a plus.
- Cross-functional Collaboration: Work closely with QA, development, DBAs, and data governance teams to align test data strategies with compliance requirements. Ability to document TDM processes, standards, and contribute to building repeatable, scalable test data provisioning pipelines.
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
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