Fractional Lead Performance Tester
Gofractional, Holmdel, NJ, United States
Role
Who you are
Proven experience mentoring and coordinating testing efforts across large, distributed engineering teams (e.g., conducting code reviews, guiding SDETs through framework adoption, and managing cross-team test schedules)
Strong hands‑on experience with AWS cloud services (EC2, ECS, RDS, API Gateway) with a focus on scalability and performance optimisation
Proven expertise in performance testing tools (specifically k6, along with JMeter or Gatling), including test design, execution, and analysis at scale
Hands‑on experience with production traffic shadowing or replay tools (such as GoReplay)
Deep experience testing distributed systems, message brokers (Kafka, RabbitMQ), microservices architectures, and high‑volume, low‑latency APIs
Solid backend programming and scripting skills in Python, Java, or TypeScript to build custom performance frameworks and tooling
Strong understanding of system design, concurrency, throughput, latency, and fault tolerance principles
Experience implementing performance testing within CI/CD pipelines (Jenkins, GitHub Actions) and enabling continuous performance feedback loops
Hands‑on experience with observability and monitoring tools (Grafana, Coralogix, PMM) for performance analysis and diagnostics
Experience working within Agile environments and translating performance insights into actionable engineering outcomes
Demonstrable hands‑on experience in backend performance engineering and automation using Python, Java, or TypeScript
Proven track record of performance, scalability, and resilience testing in AWS‑based cloud‑native systems
Strong experience designing large‑scale performance test strategies and leading QA/SDET teams to execute them
Deep understanding of API performance testing, integration testing, and system‑level non‑functional validation
Solid grasp of system architecture, distributed systems behaviour, and non‑functional testing methodologies
Experience with observability, monitoring, and log analysis tools
Familiarity with RESTful APIs and event‑driven systems
There’s no perfect candidate. You don't need all the preferred qualifications to make a valuable impact on our team. Our employees and customers come from diverse backgrounds, so if you're passionate about what you could achieve at Vonage, we'd love to hear from you
What the job involves
Define and lead the performance engineering strategy across high‑availability, cloud‑native telecom platforms
Lead, train, and coordinate a distributed guild of SDETs across multiple feature teams, guiding them to build, maintain, and execute performance scripts (k6) within their fractional sprint capacity
Design, develop, and evolve scalable backend performance frameworks using k6, Python, Java, or TypeScript, focusing entirely on APIs, databases, and infrastructure
Implement and manage production traffic replay strategies (e.g., GoReplay) and complex multi‑tenant test data generation to accurately recreate realistic production contention and load profiles
Own and drive performance, load, stress, endurance, scalability, and resilience testing, including chaos engineering practices (e.g., using AWS Fault Injection Simulator)
Validate real‑time communication systems, event‑driven architectures (Kafka, RabbitMQ), and high‑throughput distributed systems under production‑like conditions
Integrate performance testing into CI/CD pipelines, enabling continuous performance validation, shift‑left practices, and automated PR blocking for latency degradation
Leverage observability tooling (Grafana, CloudWatch, Coralogix, VictoriaMetrics, PMM) to monitor, analyse, and troubleshoot system performance
Establish performance benchmarks, SLAs, SLOs, and error budgets aligned with business and system requirements
Collaborate with architecture and data teams to identify bottlenecks, validate database architectures (e.g., MySQL, Tungsten), and present evidence‑based investment proposals
Analyse and optimise performance across both legacy monolith systems (requiring integrated load testing) and modern microservices architectures
#J-18808-Ljbffr
Who you are
Proven experience mentoring and coordinating testing efforts across large, distributed engineering teams (e.g., conducting code reviews, guiding SDETs through framework adoption, and managing cross-team test schedules)
Strong hands‑on experience with AWS cloud services (EC2, ECS, RDS, API Gateway) with a focus on scalability and performance optimisation
Proven expertise in performance testing tools (specifically k6, along with JMeter or Gatling), including test design, execution, and analysis at scale
Hands‑on experience with production traffic shadowing or replay tools (such as GoReplay)
Deep experience testing distributed systems, message brokers (Kafka, RabbitMQ), microservices architectures, and high‑volume, low‑latency APIs
Solid backend programming and scripting skills in Python, Java, or TypeScript to build custom performance frameworks and tooling
Strong understanding of system design, concurrency, throughput, latency, and fault tolerance principles
Experience implementing performance testing within CI/CD pipelines (Jenkins, GitHub Actions) and enabling continuous performance feedback loops
Hands‑on experience with observability and monitoring tools (Grafana, Coralogix, PMM) for performance analysis and diagnostics
Experience working within Agile environments and translating performance insights into actionable engineering outcomes
Demonstrable hands‑on experience in backend performance engineering and automation using Python, Java, or TypeScript
Proven track record of performance, scalability, and resilience testing in AWS‑based cloud‑native systems
Strong experience designing large‑scale performance test strategies and leading QA/SDET teams to execute them
Deep understanding of API performance testing, integration testing, and system‑level non‑functional validation
Solid grasp of system architecture, distributed systems behaviour, and non‑functional testing methodologies
Experience with observability, monitoring, and log analysis tools
Familiarity with RESTful APIs and event‑driven systems
There’s no perfect candidate. You don't need all the preferred qualifications to make a valuable impact on our team. Our employees and customers come from diverse backgrounds, so if you're passionate about what you could achieve at Vonage, we'd love to hear from you
What the job involves
Define and lead the performance engineering strategy across high‑availability, cloud‑native telecom platforms
Lead, train, and coordinate a distributed guild of SDETs across multiple feature teams, guiding them to build, maintain, and execute performance scripts (k6) within their fractional sprint capacity
Design, develop, and evolve scalable backend performance frameworks using k6, Python, Java, or TypeScript, focusing entirely on APIs, databases, and infrastructure
Implement and manage production traffic replay strategies (e.g., GoReplay) and complex multi‑tenant test data generation to accurately recreate realistic production contention and load profiles
Own and drive performance, load, stress, endurance, scalability, and resilience testing, including chaos engineering practices (e.g., using AWS Fault Injection Simulator)
Validate real‑time communication systems, event‑driven architectures (Kafka, RabbitMQ), and high‑throughput distributed systems under production‑like conditions
Integrate performance testing into CI/CD pipelines, enabling continuous performance validation, shift‑left practices, and automated PR blocking for latency degradation
Leverage observability tooling (Grafana, CloudWatch, Coralogix, VictoriaMetrics, PMM) to monitor, analyse, and troubleshoot system performance
Establish performance benchmarks, SLAs, SLOs, and error budgets aligned with business and system requirements
Collaborate with architecture and data teams to identify bottlenecks, validate database architectures (e.g., MySQL, Tungsten), and present evidence‑based investment proposals
Analyse and optimise performance across both legacy monolith systems (requiring integrated load testing) and modern microservices architectures
#J-18808-Ljbffr