Quality Assurance Lead Automation

Project Description:

One of the world's largest providers of products and services to the energy industry has a need to develop and support enterprise systems in the Oil and Gas domain.

We are looking for a highly motivated and self-organized QA automation engineer to join our team and integrate the automation process into the existing SDLC.

Responsibilities:

Lead quality assurance strategy and execution for web applications deployed on AWS and Azure cloud platforms. Drive test automation initiatives, achieving >
80% coverage, mentor junior QA engineers, and ensure delivery excellence across the software development lifecycle. Collaborate with Product, Development, and DevOps teams to embed quality practices from design through production deployment.

Mandatory Skills Description:

• 5–7 years of QA experience for web applications in Agile/Scrum
• Web testing: functional, regression, integration/system testing;
  E2E, smoke/sanity, exploratory, risk-based testing
• Test automation (2+ years) with Cypress using JavaScript/TypeScript
• REST API testing (Postman, REST Assured, or similar);
  validation of status codes/schemas/error handling;
  auth testing (OAuth2/JWT/SSO)
• CI/CD integration and automated test execution in pipelines (GitLab CI, Azure DevOps Pipelines, or Jenkins)
• Cloud deployment validation on AWS and Azure
• Test/defect management tools (Azure DevOps Test Plans/Boards or equivalent)
• Version control: Git (GitLab/GitHub)
• Scripting and data validation: Python and/or Bash;
  basic SQL for database checks
• Leadership: driving QA initiatives, mentoring, defining quality gates, defect triage

Nice-to-Have Skills Description:

• Performance/load testing (k6, JMeter, Gatling)
• Security testing awareness (OWASP Top 10;
  Burp Suite / OWASP ZAP / Snyk)
• Docker/Kubernetes validation testing
• Observability/monitoring tools (CloudWatch, Azure Monitor, Datadog, New Relic, ELK/Splunk)
• GraphQL API testing and/or contract testing
• Experience with large datasets/ETL validation, Kafka/event-driven systems, or geospatial data testing
• Domain exposure to Oil & Gas / Energy software is a plus