QU
QualysLead Performance QA Engineer
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Before you apply
LocationPune
Work modehybrid
Typefull-time
SeniorityLead
Experience7+ yrs
Company size1,001–5,000 people
PostedNov 2, 2026 · 5d ago
Verified live10h ago
At a glanceSummarised by Seekless from the posting.
7+ years of experience in Performance Testing and Performance Engineering
Proven experience leading performance initiatives for enterprise-scale applications
Strong understanding of distributed systems and cloud-native architectures
Kubernetes (K8s) and containerized environments
Microservices architecture
Apache Kafka
API performance testing and diagnostics
Redis
Oracle Database
Elasticsearch
Apache Spark
Linux system performance analysis
Experience with one or more: JMeter, Gatling, LoadRunner, k6, Locust, BlazeMeter
Hands-on experience with Grafana, Prometheus, Kibana, Elastic Stack, Dynatrace, AppDynamics, OpenTelemetry
Strong scripting/programming experience in Python
Strong scripting/programming experience in Java
Skills
Kubernetes
Kafka
Redis
Oracle Database
Elasticsearch
Apache Spark
Python
Java
JMeter
Gatling
LoadRunner
k6
Locust
BlazeMeter
Grafana
Prometheus
Kibana
Elastic Stack
Dynatrace
AppDynamics
OpenTelemetry
REST
GraphQL
About the company
Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
Performance Engineering Lead
Location: Pune / Hybrid (3 days in office)
Experience: 7+ Years
Employment Type: Full-Time
About the Role
We are looking for an experienced and highly motivated Performance Engineering Lead to drive performance validation, scalability assessment, and performance optimization across a modern cloud-native platform. The ideal candidate will have strong expertise in distributed microservices architectures, Kubernetes environments, messaging systems, APIs, big data workloads, and performance troubleshooting.
The role requires both hands-on technical excellence and leadership capabilities to plan, execute, analyze, and drive performance initiatives across release cycles while collaborating closely with development, architecture, operations, and customer-facing teams.
Key Responsibilities
Performance Strategy & Leadership
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Own performance engineering activities across multiple releases and product roadmaps.
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Define performance testing scope, objectives, workload models, success criteria, and capacity planning requirements.
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Plan, track, and deliver performance testing activities within release timelines.
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Provide regular performance status updates, risk assessments, and recommendations to stakeholders.
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Mentor and guide performance engineers and establish performance engineering best practices.
Performance Testing & Engineering
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Design and execute performance, load, stress, endurance, scalability, spike, and capacity tests.
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Validate performance of cloud-native applications running on Kubernetes (K8s).
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Build realistic workload models that simulate production-scale traffic and customer usage patterns.
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Establish performance baselines and continuously improve system scalability and reliability.
Microservices Performance Analysis
Perform detailed root cause analysis and optimization recommendations for applications leveraging:
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Kubernetes-based microservices
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Kafka-based event-driven architectures
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REST and GraphQL APIs
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Redis caching layers
•
Oracle databases
•
Elasticsearch clusters
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Spark-based batch and streaming workloads
Analyze system behavior across:
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CPU utilization
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Memory consumption
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Thread utilization
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Garbage collection
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Network latency
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Resource contention
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Database bottlenecks
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Cache efficiency
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Message processing delays
Kafka & Messaging Performance
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Design and execute load testing for Kafka-based service-to-service messaging systems.
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Analyze consumer lag, throughput, partition distribution, batching efficiency, and message processing latency.
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Tune Kafka producer, broker, and consumer configurations to optimize performance.
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Identify bottlenecks and provide recommendations to engineering teams for scalability improvements.
API Performance Engineering
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Validate latency, throughput, concurrency, error rates, and service-level objectives (SLOs).
•
Perform end-to-end performance analysis across distributed API ecosystems.
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Identify bottlenecks in service interactions and recommend optimizations.
Spark Performance Optimization
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Analyze Spark batch and streaming job performance.
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Investigate executor utilization, partitioning strategies, shuffle operations, memory management, and query execution plans.
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Recommend performance improvements to reduce execution time and infrastructure costs
Performance Diagnostics & Optimization
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Conduct deep-dive investigations into production and pre-production performance issues.
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Collaborate with developers to identify root causes and implement fixes.
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Review architecture and code changes from a scalability and performance perspective.
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Recommend improvements in application design, infrastructure configuration, caching, database queries, and messaging patterns.
Customer issues:
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Investigate customer-reported performance and scalability issues.
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Reproduce production scenarios and provide actionable recommendations.
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Work with support and engineering teams to ensure timely resolution of customer-impacting performance problems.
Test Data & Automation
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Design and develop scalable test data generation frameworks.
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Create automation utilities and performance engineering tools.
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Develop scripts and utilities using Python, Java, or similar programming languages to support performance testing and analysis.
Required Skills & Qualifications
Experience
•
7+ years of experience in Performance Testing and Performance Engineering.
•
Proven experience leading performance initiatives for enterprise-scale applications.
•
Strong understanding of distributed systems and cloud-native architectures.
Technical Expertise
•
Kubernetes (K8s) and containerized environments
•
Microservices architecture
•
Apache Kafka
•
API performance testing and diagnostics
•
Redis
•
Oracle Database
•
Elasticsearch
•
Apache Spark
•
Linux system performance analysis
Performance Testing Tools
Experience with one or more:
•
JMeter
•
Gatling
•
LoadRunner
•
k6
•
Locust
•
BlazeMeter
Monitoring & Observability
Hands-on experience with:
•
Grafana
•
Prometheus
•
Kibana
•
Elastic Stack
•
Dynatrace
•
AppDynamics
•
OpenTelemetry
Programming & Automation
Strong scripting/programming experience in:
•
Python
•
Java