
▷ [3 Days Left] Test Data Management
3 weeks ago
Job Description
Job Overview:
We are seeking a Performance Engineering Data Specialist to support the Performance Engineering team. This role focuses on data aggregation, multi-source data acquisition, and test data management to meet non-functional testing requirements. The ideal candidate will work with large datasets, automation scripts, and data visualization tools to optimize system performance and capacity planning.
Key Responsibilities:
- Design and implement data aggregation and reporting frameworks.
- Automate data collection and processing to streamline performance testing.
- Support predictive modeling for capacity planning and performance analysis.
- Develop and maintain data pipelines and architectures.
- Ensure data quality and integrity for accurate test results.
- Identify appropriate test data conditioning to meet non-functional testing requirements.
- Develop data visualizations (Tableau, Power BI) to support decision-making.
- Work with cloud-based infrastructure and containerized applications.
- Stay updated with the latest trends in data management, performance testing, and DevOps.
Requirements:
- 3-6 years experience in data analysis and reporting.
- Strong programming skills (Python, Java).
- 2-4 years experience in data visualization (Tableau, Power BI).
- Experience working with large datasets, cloud infrastructure, and containerized applications.
- Strong understanding of data aggregation, test data management, and reporting.
- 1-3 years experience in data pipeline development.
- Excellent problem-solving skills and attention to detail.
Preferred Qualifications:
- 3-5 years experience with performance testing tools (JMeter, Gatling, LoadRunner).
- Knowledge of container orchestration platforms (Kubernetes).
- Experience with DevOps and CI/CD (Jenkins, GitHub).
- Experience with IT service management frameworks (ITIL).
- Familiarity with machine learning and statistical modeling.
- Knowledge of cloud-based data platforms (AWS Redshift, Google Big Query).
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