Job Title: Performance Test Lead
\nLocation: Iselin, NJ (hybrid)
\nEmployment Type: W2 Contract
\n \nCore Tools: LoadRunner, JMeter, AppDynamics, Splunk
\nTech Focus: Java, Kafka, Microservices, Batch Systems
\nProgramming: C, Java
\n \nSummary:
\nPerformance Engineering lead with expertise in end-to-end performance testing and engineering for Java-based microservices and batch-processing workloads. Mot just an executor, drives the full lifecycle from requirement discovery to test strategy, execution, analysis, and tuning recommendations. Highly self-sufficient, proactive, and skilled at owning outcomes without constant direction.
\n \nKey Skills & Strengths
\nLeadership & Collaboration
\nWorks closely with application. Platform, infrastructure, and business teams to define performance scope, SLAs/SLOs, KPIs, and success criteria.
\nLeads performance strategy discussion, clarifies ambiguous requirements, and translates them into measurable workloads.
\nCommunicates complex technical findings clearly to developers, managers, and business stakeholders.
\nSelf-Driven & Ownership Mindset
\n \nOperates independently, identifies work, defines the approach, and executed end-to-end.
\nDrives performance analysis and bottleneck without waiting for direction.
\nBuilds test plans, scenarios, data models, and monitoring dashboards autonomously.
\nRaises risks early and provides actionable tuning recommendations.
\nPerformance Engineering Expertise
\n \nGather Performance Testing Requirements. Create and execute performance test strategy and test plan, interfacing with all stakeholders.
\nLoadRunner expert ( Web Services, Java Vuser) and worked with Jmeter/Blazemeter tool
\nStrong scripting capability, including advanced correlation, parameterization, think-time modeling, error handling, custom logic, and data-drive frameworks.
\nDeep knowledge of Java performance tuning, GC behavior, thread/heap analysis.
\nSolid understanding of microservices patterns, REST APIs, async workflows, and batch processing.
\nSkilled in designing and executing load, stress, Endurance, and scalability tests.
\nShould have conducted Chaos experiments and used AI /GHCP across the PT lifecycle.
\nCloud-Native & Container Platforms
\n \nExperience with Kubernetes/OpenShift(OCP) for performance testing microservices.
\nCapable of analyzing prod-level CPU/memory usage, HPA behavior, and autoscaling performance.
\nExperienced with evaluating limits/requests, node saturation, and cluster-level constraints.
\nMonitoring & Diagnostics
\n \nAppDynamics: Flow maps, BT triage, transaction snapshots, hotspot identification, backend call profiling, and bottleneck isolation (DB, thread pools, async calls, dependencies).
\nSplunk: Log analysis, anomaly detection, custom queries, and dashboard creation.
\nProgramming & Scripting
\n \nC for LoadRunner scripting: Java for API/microservice performance; Bash/Python for automation and data processing.
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