Test Automation Engineer

apreel został założony w kwietniu 2010 roku przez przyjaciół, których marzeniem było stworzenie własnego software house'u. Firma rozszerzyła działalność o leasing ekspertów IT, co obecnie stanowi główny filar jej działalności. Pasją apreela jest tworzenie autorskich rozwiązań informatycznych i ich ciągłe doskonalenie.

• 5+ years of software quality engineering or test automation experience, including at least 2 years of data-centric validation.
• 2+ years of hands-on experience with Robot Framework, including reusable resources, custom Python keyword libraries, parameterized testing, and output analysis.
• Strong Python programming skills for parsing, transformation, JSON traversal, numerical comparison, and automated validation.
• Experience writing SQL for data reconciliation, quality analysis, regression trending, and defect investigation.
• Experience validating source-to-target mappings across JSON, CSV, XML, XLS/XLSX, and structured or semi-structured text formats.
• Knowledge of JSON Schema, semantic data models, controlled vocabularies, and schema-driven validation; Allotrope ASM experience preferred.
• Experience with smoke, functional, regression, and UAT testing, including defect lifecycle management and root cause analysis.
• Experience with Git, GitHub Actions or equivalent CI/CD tooling, containerized execution, dependency management, and automated report publishing.
• Familiarity with Jira, Xray, Agile delivery, test evidence management, and regulated or GxP laboratory environments.

Nice to have:

• Experience with Robot Framework, SQL, JSON, databases, CI/CD, and Git.

• Design, build, maintain and run Robot Framework validation suites for instrument data converted to Allotrope Simple Model (ASM) JSON.
• Translate business requirements, field mappings, SOPs and validation standards into automated schema, mapping, semantic and formatting checks.
• Develop Python readers, custom Robot Framework keywords and reusable validation libraries for CSV, XML, XLS/XLSX, JSON, and instrument-specific formats.
• Perform smoke, functional, regression, UAT and cross-version testing across converter releases and instrument datasets.
• Conduct root-cause analysis to distinguish converter defects, source-data issues, schema changes and test automation defects.
• Analyze validation results using SQL, DuckDB and Parquet to identify findings.
• Prepare and publish test summary, defect summary, HTML/JSON and trend reports for stakeholders.
• Maintain CI/CD execution and reporting through GitHub Actions, containerized test environments, Artifactory, Jira and Xray.