Test Data Management Engineer
do 150 PLN/ godz.B2B
SeniorFull-time·B2B
#441618·Dodano wczoraj·1
Źródło: emagineTech Stack / Keywords
SQLPythonPowerShellJavaCI/CDDevOpsTricentis ToscaKubernetesAPI testing
Firma i stanowisko
Banking industry role based in Poland, requiring hybrid work presence in Warsaw or Gdynia/Gdańsk.
Wymagania
- 8+ years in Test Data Management or Test Automation.
- Strong SQL and database knowledge.
- Knowledge of mainframe systems and setups.
- Hands-on experience with relational databases, data extraction and transformation.
- Test data generation, masking, cloning, and subsetting expertise.
- Hands-on implementation of TDM solutions.
- Experience working in Agile teams.
- Scripting skills (Python, PowerShell, Java, or similar).
- Understanding of CI/CD processes and DevOps practices.
- Experience with synthetic data generation tools and test automation tools.
- Fluent in English.
Nice to have:
- Experience with Tricentis Tosca TDM, Curiosity Software, Delphix, Informatica TDM.
- Knowledge of the financial services domain.
- API testing experience.
- Kubernetes and cloud platform knowledge.
- AI-assisted test data creation.
- Experience supporting large-scale E2E customer journey testing.
Obowiązki
- Execute the test data strategy and build automated solutions.
- Create and maintain reusable test data assets.
- Develop automated test data provisioning solutions and self-service data delivery mechanisms.
- Implement data masking and anonymization routines ensuring GDPR and internal policy compliance.
- Create synthetic test datasets, including edge-case and negative test data, and maintain business-realistic data combinations.
- Provision test data to non-production environments, manage data refresh, cloning, and subsetting to support parallel testing across multiple teams.
- Integrate test data generation into automation frameworks to enable CI/CD-driven test data provisioning and support automated regression execution.
- Support automated, integration, and end-to-end (E2E) testing.
- Monitor data availability and quality, and resolve data-related defects and issues.
- Document processes, standards, and data dependencies.
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