QA Automation + Performance testing Engineer - Chicago IL (Day 1 Onsite)

Title: QA Automation+ Performance testing Engineer Location: Chicago, IL (Day 1 Onsite) Note: Need 12+ Years candidates. Job Description Hands on experience in software test automation and performance engineering (or equivalent), covering AWS and on‑prem platforms. Strong coding skills in one or more: Java, Python, JavaScript, Groovy, TypeScript. Hands‑on experience with testing tools: Cypress, Selenium, JMeter, Blazemeter or equivalent tools. Working proficiency with development toolsets and CI/CD pipelines: Jenkins, GitHub, Bitbucket, IntelliJ IDEA, VS Code. Familiarity with distributed services and microservices architecture in AWS; Kubernetes; databases such as Oracle and MongoDB. Experience with observability tooling and metrics: Dynatrace, Geneos, Splunk, Grafana; ability to interpret system/resource metrics and application telemetry. Familiar with Agile Methodology; ability to work independently with strong analytical, communication, and documentation skills; ability to influence cross‑functional teams. Preferred Qualifications Experience in financial services; domain knowledge in Receivables or Lockbox. Performance tuning across JVM/.NET, databases, and front‑end assets. Experience leveraging GenAl to accelerate test creation, analysis, or documentation; define and own the automation strategy and roadmap; design, build, and maintain robust test automation frameworks; implement reliable automated tests for UI, API, microservices, and data workflows; integrate automated tests into CI/CD; establish quality gates, automated reporting, and release readiness criteria. Lead test strategy and coverage for functional and non‑functional requirements; set and enforce standards for test data management and environment readiness to ensure deterministic, reproducible runs. Key Skills Java, Python, JavaScript, Groovy, TypeScript. Cypress, Selenium, JMeter, Blazemeter. CI/CD: Jenkins, GitHub, Bitbucket, IntelliJ IDEA, VS Code. AWS, Kubernetes. Databases: Oracle, MongoDB, SQL, NoSQL. Observability: Dynatrace, Geneos, Splunk, Grafana. Performance testing lifecycle: requirements gathering, workload modeling, environment setup, execution (load and stress). #J-18808-Ljbffr Tech Mirrors