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