Automation Test Analyst

RPA AUTOMATION TESTER

Must have experience with Power Automate

Key Responsibilities

End-to-End Automation Assurance

• Own quality assurance across the full automation lifecycle, from document ingestion through AI extraction, workflow processing, API integrations, and ERP updates.
• Design and execute testing strategies that validate business outcomes rather than individual system components in isolation.
• Verify that information extracted from vendor documents is correctly interpreted, transformed, and persisted throughout the automation workflow.
• Ensure automation solutions remain reliable when document formats, vendor templates, business rules, or downstream systems change

AI & Document Extraction Validation

• Define expected outputs for document extraction processes and maintain representative datasets covering real-world business scenarios.
• Validate extraction accuracy at document, field and line-item level.
• Build automated comparison frameworks that compare expected outputs against actual outputs and identify discrepancies.
• Measure extraction quality across vendors, document types and business processes.
• Identify extraction failure patterns and collaborate with developers to improve automation accuracy.
• Maintain benchmark datasets and golden test cases used to evaluate future releases.

Automation & Workflow Testing

• Design automated regression suites covering Automation Anywhere workflows, API integrations, business rules and ERP interactions.
• Validate processing of both standard and non-standard documents, including incomplete, malformed and edge-case inputs.
• Test workflow exception handling, ensuring failures are correctly identified, routed and reported.
• Verify business rule execution including pricing, quantities, dates, discounts, serial numbers and vendor-specific mappings.
• Build regression coverage for all previously identified production incidents and escaped defects.

Automated Validation Frameworks

• Develop and maintain automated validation solutions using Python, APIs and data comparison techniques.
• Create deterministic comparison frameworks capable of validating large volumes of extracted and transformed business data.
• Build automated reporting that highlights mismatches, missing values and processing anomalies.
• Establish repeatable validation approaches that reduce reliance on manual testing and spreadsheet-based verification.

Release Quality & Risk Management

• Define and maintain release quality gates for automation solutions.
• Establish minimum quality thresholds for extraction accuracy, regression coverage and workflow reliability.
• Prevent deployment of solutions that introduce business-critical data loss, mapping errors or processing failures.
• Support production readiness reviews and provide evidence-based recommendations for go-live decisions.

Defect Investigation & Continuous Improvement

• Reproduce production defects as automated tests before fixes are implemented.
• Build and maintain a regression library derived from real operational incidents.
• Perform root-cause analysis across automation workflows, APIs, AI extraction components, and ERP integrations.
• Work with developers, architects, and business stakeholders to drive improvements in automation quality and reliability.

Required Skills

• Strong software testing and quality assurance experience.
• Experience in testing complex integrated systems.
• Strong Python skills for data validation and automation.
• Experience working with REST APIs and system integrations.
• Experience building automated test frameworks.
• Strong analytical and troubleshooting skills.
• Experience working with structured and semi-structured data.
• Ability to translate business processes into measurable quality controls.

Desirable Skills

• Automation Anywhere.
• Power Automate.
• AI / LLM-powered solutions.
• Intelligent document processing.
• ERP systems such as Navision, Dynamics or SAP.
• Playwright or equivalent browser automation tools.
• Azure DevOps CI/CD pipelines.
• Data quality and data validation frameworks.

Essential

Programming & Automation

• Python (strong proficiency)
• Data validation and comparison frameworks
• API integration
• Test automation development
• Data transformation and analysis
• Pandas for large-scale validation and reporting
• SQL (strong proficiency)
• Query writing and optimisation
• Data reconciliation
• Data quality validation
• Root-cause investigation
• Git
• Branching strategies
• Pull requests
• Code reviews
• Source control best practices

Test Automation

• Playwright
• Browser automation
• End-to-end workflow validation
• UI verification
• Automated evidence capture
• API Testing
• REST APIs
• JSON validation
• Postman
• Automated API test frameworks
• Test Framework Development
• PyTest or equivalent
• Data-driven testing
• Regression framework design
• Automated reporting

Data Validation & Analysis

• Pandas
• CSV, JSON, and XML processing
• Dataset comparison techniques
• Data quality assessment
• Automated reconciliation frameworks
• Root-cause analysis using structured data