{"id":3604312,"url":"https://alion.io/job/qualys-lead-performance-qa-engineer","title":"Lead Performance QA Engineer","company":{"id":18966,"name":"Qualys","domain":"qualys.com","url":"https://alion.io/company/qualys","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":95,"open_postings":3,"ghost_share":0,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":62,"computed_at":"2026-11-03T05:54:40Z"}},"role":"QA","role_family":"QA","seniority":"lead","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Pune, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Apache Kafka","optional":false},{"name":"AppDynamics","optional":false},{"name":"Dynatrace","optional":false},{"name":"ElasticSearch","optional":false},{"name":"Gatling","optional":false},{"name":"Grafana","optional":false},{"name":"GraphQL","optional":false},{"name":"Java","optional":false},{"name":"JMeter","optional":false},{"name":"k6","optional":false},{"name":"Kibana","optional":false},{"name":"Kubernetes","optional":false},{"name":"Linux","optional":false},{"name":"Locust","optional":false},{"name":"OpenTelemetry","optional":false},{"name":"Oracle","optional":false},{"name":"Prometheus","optional":false},{"name":"Python","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Shuffle","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-11-02T11:00:28Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T01:01:31Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!\nPerformance Engineering Lead\nLocation: Pune / Hybrid (3 days in office)\nExperience: 7+ Years\nEmployment Type: Full-Time\nAbout the Role\nWe 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.\nThe 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.\nKey Responsibilities\nPerformance Strategy & Leadership\nOwn performance engineering activities across multiple releases and product roadmaps.\nDefine performance testing scope, objectives, workload models, success criteria, and capacity planning requirements.\nPlan, track, and deliver performance testing activities within release timelines.\nProvide regular performance status updates, risk assessments, and recommendations to stakeholders.\nMentor and guide performance engineers and establish performance engineering best practices.\n\nPerformance Testing & Engineering\nDesign and execute performance, load, stress, endurance, scalability, spike, and capacity tests.\nValidate performance of cloud-native applications running on Kubernetes (K8s).\nBuild realistic workload models that simulate production-scale traffic and customer usage patterns.\nEstablish performance baselines and continuously improve system scalability and reliability.\nMicroservices Performance Analysis\nPerform detailed root cause analysis and optimization recommendations for applications leveraging:\nKubernetes-based microservices\nKafka-based event-driven architectures\nREST and GraphQL APIs\nRedis caching layers\nOracle databases\nElasticsearch clusters\nSpark-based batch and streaming workloads\nAnalyze system behavior across:\nCPU utilization\nMemory consumption\nThread utilization\nGarbage collection\nNetwork latency\nResource contention\nDatabase bottlenecks\nCache efficiency\nMessage processing delays\nKafka & Messaging Performance\nDesign and execute load testing for Kafka-based service-to-service messaging systems.\nAnalyze consumer lag, throughput, partition distribution, batching efficiency, and message processing latency.\nTune Kafka producer, broker, and consumer configurations to optimize performance.\nIdentify bottlenecks and provide recommendations to engineering teams for scalability improvements.\nAPI Performance Engineering\nValidate latency, throughput, concurrency, error rates, and service-level objectives (SLOs).\nPerform end-to-end performance analysis across distributed API ecosystems.\nIdentify bottlenecks in service interactions and recommend optimizations.\nSpark Performance Optimization\nAnalyze Spark batch and streaming job performance.\nInvestigate executor utilization, partitioning strategies, shuffle operations, memory management, and query execution plans.\nRecommend performance improvements to reduce execution time and infrastructure costs\nPerformance Diagnostics & Optimization\nConduct deep-dive investigations into production and pre-production performance issues.\nCollaborate with developers to identify root causes and implement fixes.\nReview architecture and code changes from a scalability and performance perspective.\nRecommend improvements in application design, infrastructure configuration, caching, database queries, and messaging patterns.\nCustomer issues:\nInvestigate customer-reported performance and scalability issues.\nReproduce production scenarios and provide actionable recommendations.\nWork with support and engineering teams to ensure timely resolution of customer-impacting performance problems.\nTest Data & Automation\nDesign and develop scalable test data generation frameworks.\nCreate automation utilities and performance engineering tools.\nDevelop scripts and utilities using Python, Java, or similar programming languages to support performance testing and analysis.\nRequired Skills & Qualifications\nExperience\n7+ years of experience in Performance Testing and Performance Engineering.\nProven experience leading performance initiatives for enterprise-scale applications.\nStrong understanding of distributed systems and cloud-native architectures.\nTechnical Expertise\nKubernetes (K8s) and containerized environments\nMicroservices architecture\nApache Kafka\nAPI performance testing and diagnostics\nRedis\nOracle Database\nElasticsearch\nApache Spark\nLinux system performance analysis\nPerformance Testing Tools\nExperience with one or more:\nJMeter\nGatling\nLoadRunner\nk6\nLocust\nBlazeMeter\nMonitoring & Observability\nHands-on experience with:\nGrafana\nPrometheus\nKibana\nElastic Stack\nDynatrace\nAppDynamics\nOpenTelemetry\nProgramming & Automation\nStrong scripting/programming experience 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