Automated Validation Tester – Laboratory Data, Robot Framework

This is a fully remote position, open to applicants in Czechia.

📋 Description

• Create, develop, manage, and execute validation suites using Robot Framework for laboratory instrument data formatted as Allotrope Simple Model (ASM) JSON.

• Convert business requirements, source-to-target mappings, standard operating procedures (SOPs), and validation standards into automated checks for schema, mapping, semantics, and data formatting.

• Build Python readers, custom keywords for Robot Framework, and reusable libraries for validation.

• Validate data across various formats including JSON, CSV, XML, XLS/XLSX, structured text, and specific formats related to instruments.

• Conduct smoke, functional, regression, user acceptance testing (UAT), and testing across different versions of converters and laboratory datasets.

• Perform root-cause analysis to identify converter defects, source data issues, schema modifications, and automation failures.

• Ensure comprehensive end-to-end test traceability, which includes mapping identifiers, defect/finding keys, execution provenance, and verifiable test evidence.

• Utilize SQL, DuckDB, and Parquet to analyze validation outcomes and detect new, recurring, resolved, reopened, and regressed findings.

• Compile and distribute Test Summary, Defect Summary, HTML/JSON, and trend reports.

• Sustain automated execution and reporting through platforms such as GitHub Actions, containerized environments, Artifactory, Jira, and Xray.

• Engage in test reviews, troubleshooting, defect triage, documentation, and technical discussions within a globally distributed team.

⛳️ Requirements

• Over 5 years of experience in software quality engineering or test automation.

• A minimum of 2 years of experience in data-centric validation and testing.

• At least 2 years of practical experience with Robot Framework.

• Familiarity with reusable resources and libraries, custom Python keyword libraries, parameterized/data-driven testing, and analysis of Robot Framework outputs.

• Proficient Python development skills for tasks such as parsing, data transformation, JSON traversal, numerical comparisons, and automated validation.

• Strong SQL skills for data reconciliation, quality analysis, regression trending, and investigation of defects.

• Experience validating source-to-target mappings across JSON, CSV, XML, XLS/XLSX, and structured or semi-structured data.

• Knowledge of JSON Schema, semantic data models, controlled vocabularies, and schema-driven validation techniques.

• Experience with smoke, functional, regression, and UAT testing, including management of defect lifecycles and root-cause analysis.

• Familiarity with Git and CI/CD processes, preferably using GitHub Actions.

• Experience with containerized test execution, dependency management, and automated reporting mechanisms.

• Proficient in using Jira and Xray.

• Excellent written and verbal communication skills in English.

• Highly desirable: Knowledge of Allotrope Simple Model (ASM) or the wider Allotrope ecosystem.

• Highly desirable: Experience working with scientific or laboratory instrument data.

• Highly desirable: Background in the pharmaceutical, biotechnology, life sciences, or other regulated sectors.

• Highly desirable: Understanding of GxP validation and the need for audit-ready test evidence.

• Highly desirable: Familiarity with DuckDB and Parquet.

• Bachelor’s degree in IT, Computer Science, Engineering, or a related field; or equivalent relevant professional experience.

🏝️ Benefits

• Freelance / Contract.

• 40 hours per week.

• Remote work as specified in the job posting.

• Anticipated start date: October/November 2026.