QA Automation + Performance testing Engineer – Chicago IL; Onsite

Title: QA Automation+ Performance testing Engineer
Location:
Chicago, IL (Day 1 Onsite)

Note:
Need 12+ Years candidates.

• 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, Type Script.
• Hands‑on experience with testing tools:
  Cypress, Selenium, JMeter, Blazemeter or equivalent tools.
• Working proficiency with development toolsets and CI/CD pipelines:
  Jenkins, Git Hub, 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.

• Experience in financial services; domain knowledge in Receivables or Lockbox.
• Performance tuning across JVM/.NET, databases, and front‑end assets.
• Experience leveraging Gen Al 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.

• Java, Python, JavaScript, Groovy, Type Script.
• Cypress, Selenium, JMeter, Blazemeter.
• CI/CD:
  Jenkins, Git Hub, Bitbucket, IntelliJ IDEA, VS Code.
• AWS, Kubernetes.
• Databases:
  Oracle, MongoDB, SQL, No
  
  SQL.
• Observability:
  Dynatrace, Geneos, Splunk, Grafana.
• Performance testing lifecycle: requirements gathering, workload modeling, environment setup, execution (load and stress).