Automated Validation Tester – Laboratory Data / Robot Framework

We are looking for an experienced Automated Validation Tester to join the PLA sub-team within a global digital and scientific data program. The project focuses on the automated validation of laboratory instrument data converted into Allotrope Simple Model (ASM) JSON. The successful candidate will design and maintain automated validation frameworks that ensure scientific data is accurately converted, mapped, structured, and validated across multiple laboratory instruments and converter releases. This is a highly technical, data-focused QA role combining Robot Framework, Python, SQL, JSON/schema validation, test automation, and scientific laboratory data.

Key

Responsibilities Design, build, maintain, and execute Robot Framework validation suites for laboratory instrument data converted to Allotrope Simple Model (ASM) JSON. Translate business requirements, source-to-target mappings, SOPs, and validation standards into automated schema, mapping, semantic, and formatting checks. Develop Python readers, custom Robot Framework keywords, and reusable validation libraries. Validate data across JSON, CSV, XML, XLS/XLSX, structured text, and instrument-specific formats. Perform smoke, functional, regression, UAT, and cross-version testing across converter releases and laboratory datasets. Conduct root-cause analysis to distinguish between converter defects, source-data issues, schema changes, and automation defects. Maintain end-to-end test traceability, including mapping identifiers, defect/finding keys, execution provenance, and auditable test evidence. Use SQL, DuckDB, and Parquet to analyze validation results and identify new, recurring, resolved, reopened, and regressed findings. Prepare and publish Test Summary, Defect Summary, HTML/JSON, and trend reports. Maintain automated execution and reporting through GitHub Actions, containerized environments, Artifactory, Jira, and Xray. Participate in test reviews, troubleshooting, defect triage, documentation, and technical meetings within a distributed international team. Requirements 5+ years of software quality engineering / test automation experience. At least 2 years of data-centric validation/testing experience. At least 2 years of hands-on Robot Framework experience, including: reusable resources and libraries custom Python keyword libraries parameterized/data-driven testing Robot Framework output analysis Strong Python development skills, particularly for parsing, transformation, JSON traversal, numerical comparison, and automated validation. Strong SQL skills for reconciliation, data-quality analysis, regression trending, and defect investigation. Experience validating source-to-target mappings across JSON, CSV, XML, XLS/XLSX, and structured/semi-structured data. Understanding of JSON Schema, semantic data models, controlled vocabularies, and schema-driven validation. Experience with smoke, functional, regression, and UAT testing, including defect lifecycle management and root-cause analysis. Experience with Git and CI/CD, preferably GitHub Actions. Experience with containerized test execution, dependency management, and automated reporting. Experience with Jira and Xray. Strong written and verbal English communication skills. Highly Desirable Experience with Allotrope Simple Model (ASM) or the broader Allotrope ecosystem. Experience working with scientific or laboratory instrument data. Experience within pharmaceutical, biotechnology, life sciences, or other regulated environments. Knowledge of GxP validation and audit-ready test evidence. Experience with DuckDB and Parquet.

Education B.A. or B.S. degree, preferably in IT, Computer Science, Engineering, or a related discipline; alternatively, equivalent relevant professional experience.

Benefits Location: Hybrid/Remote Contract Type: Freelance / Contract Start date: October/November, 2026 Time Allocation: 40 hours/week Global Pharmaceutical Company in Prague