symplr
Website:
symplr.com
Job details:
Designing comprehensive performance testing strategies, leading initiatives, and collaborating with cross-functional teams to ensure system reliability, scalability, and responsiveness across applications
Conduct thorough performance assessments, including load testing, stress testing, and capacity planning, to identify system bottlenecks and areas for improvement.
Work closely with development and operations teams to Identifying key performance indicators (KPIs) and establishing benchmarks, monitoring solutions, and dashboards that provide real-time insights into system performance.
Architect and implement scalable testing frameworks for performance, and data validation, focusing on AI and Generative AI applications.
Lead the troubleshooting and resolution of complex performance-related issues in QA, Staging, Pre-production and/or Production environments.
Provide guidance and mentorship to junior QA engineers, fostering a culture of quality and continuous learning.
Utilize industry-standard performance testing tools (e.g., JMeter, LoadRunner, Gatling) to simulate real-world scenarios and measure system performance, staying current with emerging tools and technologies in the performance testing space.
Collaborate with development, QA, and operations teams to integrate performance testing into the continuous integration and continuous deployment (CI/CD) processes, providing guidance and support to team members on performance testing best practices.
Analyze the CPU Utilization, Memory usage, Network usage, Garbage Collection to verify the performance of the applications.
Generate performance graphs, session reports, and other related documentation required for validation and analysis.
Create comprehensive performance test documentation, including test plans, test scripts, and performance analysis reports, effectively communicating performance testing results and recommendations to technical and non-technical stakeholders.
Duties & Responsibilities
Bachelor’s or Master’s degree in computer science, Engineering, or a related field.
12+ years of experience in performance testing and engineering, with a strong understanding of performance testing methodologies and tools.
Proficiency in performance testing tools such as JMeter, LoadRunner, or Gatling.
Proficiency in programming languages such as Python, Javascript, Java.
Extensive experience with cloud technologies and platforms (e.g., AWS, Azure, Google Cloud) and containerization (Docker/Kubernetes).
Strong understanding of web technologies and application architecture
Experience in Application Monitoring Tools and profiling tools like Datadog, Dynatrace, Grafana, AppDynamics, Splunk.
Strong experience with CI/CD pipelines and DevOps practices.
Experience in Applications like ElasticSearch, OpenSearch, Grafana, Kafka.
Hands-on experience with performance test simulations, performance analysis, performance tuning, performance monitoring in a microservices environment
Hands- on experience in analyzing the performance results - Capture/Analyze/Interpret performance metrics from application, database, OS, and Network.
Working knowledge of SQL and cloud Databases like MongoDB, Cosmos DB, PostgreSQL
Skills Required
Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) is a plus.
Strong understanding of data validation techniques and tools.
Demonstrated ability to analyze complex systems, identify performance bottlenecks, and provide actionable insights.
Good understanding of basic DB tuning, application server tuning and common issues around performance and scalability.
Proven track record of leading performance testing teams and drive initiatives by collaborating effectively with cross-functional teams.
Strong verbal and written communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Good understanding of computer networks and networking concepts
Agile development experience
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