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Seeking a detail-oriented and proactive QA/Test Engineer to join the client's Power Factory Automation team. This role is critical in ensuring the quality and reliability of automation scripts and data workflows used in power system studies and analysis with DIgSILENT Power Factory. The ideal candidate will have a strong foundation in power systems engineering, either through formal education or hands-on experience in the energy/utilities domain, and a solid understanding of software testing practices.

Roles and Responsibilities

• Collaborate with developers, power system engineers, and business analysts to understand testing needs and ensure domain-aligned validation.
• Define and execute test cases for automation scripts and power system study outputs (e.g., load flow, contingency analysis, fault level).
• Perform manual testing of Power Factory-based workflows and data pipelines.
• Identify, document, and track bugs and inconsistencies in data and automation logic.
• Ensure test scripts are created, maintained, and executed to meet project deliverables.
• Support UAT cycles and coordinate with stakeholders to validate deliverables.
• Contribute to continuous improvement of QA processes and testing frameworks.

Required Skill Set

• 5+ years of experience in software testing or QA roles, with mandatory exposure to the energy or utilities domaineither through professional experience or academic background in electrical/power systems engineering.
• Strong understanding of power systems concepts (e.g., load flow, fault analysis, contingency analysis).
• Familiarity with scripting languages (e.g., Python, DPL, or DSL).
• Experience with test management tools (e.g., JIRA, TestRail) and version control systems (e.g., Git).
• Strong analytical and problem-solving skills.
• Excellent communication and documentation abilities.

Nice to Have

• Hands-on experience with DIgSILENT PowerFactory or similar power system simulation tools.
• Exposure to automation testing frameworks and CI/CD pipelines.
• Knowledge of data validation techniques and working with large datasets.