[Hiring] Data Quality Manager @KOMMLINk

Role Description

For one of our clients in the pharmaceutical industry, we are looking for a freelance Data Quality Manager. The role focuses on ensuring that data is complete, consistent, connected, and fit for advanced analytics and AI-driven use cases. You will establish transparent data quality monitoring, define sustainable governance and processes, improve master data structures, and leverage modern AI capabilities to proactively identify and address data quality issues. You will work closely with business stakeholders, system experts, process owners, master data owners, and project teams to establish a scalable data quality framework and enable AI-ready data foundations.

Key Responsibilities

• Data Quality Strategy & Governance
  • Assess and visualize data quality through dashboards, scorecards, and KPIs.
  • Define data quality dimensions, business rules, and measurement methodologies.
  • Establish governance models for continuous data quality monitoring and improvement.
  • Define target states, success criteria, and measurable improvement goals.
  • Create transparent reporting mechanisms for management and operational teams.
• Data Analysis & AI-Driven Insights
  • Analyze large datasets to identify quality issues, inconsistencies, duplicates, missing data, and process weaknesses.
  • Apply AI and advanced analytics to:
    • Detect anomalies and patterns.
    • Identify root causes of data quality issues.
    • Support proactive monitoring.
    • Generate actionable recommendations.
  • Evaluate and integrate emerging AI technologies into data quality processes and monitoring solutions.
• Master Data Management
  • Identify critical master data objects and relationships.
  • Collaborate with global master data owners to establish a Single Source of Truth.
  • Define required master data structures and attributes.
  • Harmonize data definitions and standards across systems.
  • Ensure alignment between business requirements, data models, and system architecture.
• Data Modelling & Architecture
  • Design and maintain conceptual, logical, and physical data models.
  • Document data relationships, hierarchies, and dependencies.
  • Support the definition of data standards and metadata requirements.
  • Ensure data structures support business processes, reporting, AI use cases, and regulatory requirements.
• Process Design & Global Rollout
  • Define global processes and standards for data creation and maintenance.
  • Develop guidance, training materials, and supporting documentation.
  • Support global implementation and rollout activities.
  • Drive stakeholder engagement and adoption of new processes and standards.
  • Facilitate workshops with SMEs, process owners, and business representatives.
• Interface & System Integration
  • Define data requirements for interfaces and integrations.
  • Support project teams during interface implementation and rollout.
  • Ensure data quality considerations are embedded into integration design.
  • Collaborate with IT and system teams to improve data flows across the application landscape.
• Continuous Improvement
  • Establish workflows for reporting and resolving data quality issues.
  • Identify opportunities to improve user experience and data entry quality.
  • Lead root-cause investigations and define corrective and preventive actions.
  • Drive a culture of data ownership and accountability.

Qualifications

• Bachelor's or Master's degree in one of the following:
  • Information Management
  • Data Science
  • Computer Science
  • Business Informatics
  • Life Sciences
  • Related field
• 5+ years of experience in one or more of the following areas:
  • Data Quality Management
  • Data Governance
  • Data Analytics
  • Data Architecture
  • Master Data Management
• Proven experience with:
  • Data modelling
  • Data governance programs
  • Cross-functional stakeholder management
  • Global process design and rollout
  • Dashboard development and KPI frameworks

Requirements

• Strong data analysis capabilities.
• Experience with data visualization platforms such as Power BI.
• Knowledge of master data management concepts and governance frameworks.
• Experience with data quality tools and monitoring solutions.
• Understanding of system interfaces, APIs, and enterprise data architecture.
• Practical experience applying AI or Machine Learning techniques to data analysis and monitoring.

Preferred Experience

• Experience in regulated environments, particularly GxP, pharmaceutical, or healthcare.
• Knowledge of Quality Management Systems, LIMS, SAP QM, Veeva, or related enterprise platforms.
• Experience working on global transformation or digitalization programs.

Personal Competencies

• Strong analytical and problem-solving mindset.
• Ability to translate business requirements into data-driven solutions.
• Excellent workshop facilitation and stakeholder management skills.
• Strong communication and change management capabilities.
• Ability to work independently within complex global organizations.
• Hands-on mentality with a strong focus on delivery and measurable outcomes.

Expected Deliverables

• Data Quality Dashboard and KPI Framework
• Data Quality Improvement Roadmap
• Target Data Model Documentation
• Master Data Governance Recommendations
• Global Data Entry and Maintenance Processes
• Data Quality Monitoring Framework
• AI-Enabled Data Quality Analysis Concepts and Use Cases
• Site Rollout and Adoption Support Materials
• Continuous Improvement Backlog and Feedback Workflow

Start Date

01 September 2026

End Date

31 December 2026

Capacity

40 hours/week

Location

Remote