Data Quality Analyst – ADE ASM Converter Development
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Job Description
Data Quality Analyst validating scientific and laboratory data and ASM converters. Supporting data integration, traceability, and quality delivery for a global pharmaceutical company.
Responsibilities:
- Define data quality requirements, acceptance criteria, validation approaches, and test scenarios
- Support end-to-end onboarding and validation of scientific data and ASM converters
- Lead requirements and discovery sessions with Scientists, SMEs, and business stakeholders
- Analyze laboratory instrument data and define key scientific data fields
- Create and review source-to-target mappings and data transformation requirements
- Collaborate with Semantic Engineers on mapping data to the Allotrope Ontology and ASM schemas
- Validate converter outputs and ensure scientific meaning and data integrity are preserved
- Perform and coordinate source-to-target validation, data transformation verification, data quality checks, traceability testing, semantic mapping validation, and converter output validation
- Review test results, validation evidence, defects, and data quality metrics
- Support defect triage, root-cause analysis, risk assessment, and remediation
- Ensure traceability between requirements, mappings, test scenarios, and validation evidence
- Support release-readiness assessments and approval processes
- Create and review SDLC and validation documentation
- Manage risks, issues, dependencies, and delivery blockers
- Coordinate activities across Scientific, Data Engineering, Quality, Product, Architecture, and vendor teams
- Support continuous improvement of data quality processes, validation methodologies, and reusable testing assets
- Ensure adherence to data governance, SDLC, quality, and compliance requirements
Requirements:
- Bachelor's or master's degree in Computer Science, Engineering, Data Science, Information Systems, Biotechnology, or a related field, or equivalent professional experience
- 6+ years of experience in Data Engineering, Data Integration, Data Management, Data Quality, or related data-focused roles
- Strong understanding of data quality, data validation, data modeling, data mapping, data transformation, source-to-target mapping, and data traceability
- Experience defining requirements, acceptance criteria, validation approaches, and test scenarios
- Experience validating complex data transformations and integrations
- Understanding of the software development lifecycle (SDLC) and data lifecycle management
- Knowledge of data governance principles
- Experience working with non-technical stakeholders to understand business or scientific requirements
- Ability to translate business or scientific requirements into clear data and validation specifications
- Experience documenting and managing risks, issues, dependencies, and decisions
- Strong analytical and problem-solving skills
- Strong communication and stakeholder management skills
- Experience working with cross-functional teams including Engineering, Quality, Product, Business, SMEs, and external vendors
- Experience within pharmaceutical, biotechnology, life sciences, or drug discovery environments
- Experience working with scientific or laboratory data
- Understanding of laboratory workflows and laboratory instrument data
- Experience with data onboarding, integration, migration, transformation, or validation projects
- Knowledge of Allotrope Foundation standards
- Experience with Allotrope Simple Model (ASM)
- Knowledge of ontologies, semantic models, or metadata management
- Experience with Jira, Confluence, VERA, Xray, Mural, or similar tools
- Experience with automated data validation or testing frameworks
Benefits:
- Remote work arrangement
- Freelance / contract engagement
- 40 hours/week time allocation
- Opportunity to work with a global pharmaceutical company in Prague
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