Performance Test Lead

Tech Focus: Java, Kafka, Microservices, Batch Systems

Programming: C, Java

Summary:

Performance 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.

Key Skills & Strengths

Leadership & Collaboration

• Works closely with application. Platform, infrastructure, and business teams to define performance scope, SLAs/SLOs, KPIs, and success criteria.
• Leads performance strategy discussion, clarifies ambiguous requirements, and translates them into measurable workloads.
• Communicates complex technical findings clearly to developers, managers, and business stakeholders.

Self-Driven & Ownership Mindset

• Operates independently, identifies work, defines the approach, and executed end-to-end.
• Drives performance analysis and bottleneck without waiting for direction.
• Builds test plans, scenarios, data models, and monitoring dashboards autonomously.
• Raises risks early and provides actionable tuning recommendations.

Performance Engineering Expertise

• Gather Performance Testing Requirements. Create and execute performance test strategy and test plan, interfacing with all stakeholders.
• LoadRunner expert (HTTP/HTML, Web Services, Java Vuser) and worked with Jmeter/Blazemeter tool
• Strong scripting capability, including advanced correlation, parameterization, think-time modeling, error handling, custom logic, and data-drive frameworks.
• Deep knowledge of Java performance tuning, behavior, thread/heap analysis.
• Solid understanding of microservices patterns, REST APIs, async workflows, and batch processing.
• Skilled in designing and executing load, stress, Endurance, and scalability tests.
• Should have conducted Chaos experiments and used AI /GHCP across the PT lifecycle.

Cloud-Native & Container Platforms

• Experience with Kubernetes/OpenShift(OCP) for performance testing microservices.
• Capable of analyzing prod-level CPU/memory usage, HPA behavior, and autoscaling performance.
• Experienced with evaluating limits/requests, node saturation, and cluster-level constraints.

Monitoring & Diagnostics

• AppDynamics: Flow maps, BT triage, transaction snapshots, hotspot identification, backend call profiling, and bottleneck isolation (DB, thread pools, async calls, dependencies).
• Splunk: Log analysis, anomaly detection, custom queries, and dashboard creation.

Programming & Scripting

• C for LoadRunner scripting: Java for API/microservice performance; Bash/Python for automation and data processing.

Value Proposition:

A self-driven, requirements-focused Performance Engineering Lead who goes beyond test execution, capable of driving performance strategy, execution, diagnostics, and tuning across the full technology stack while collaborating effectively with application, platform, and business teams.