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Data Analyst (f/m/d) – Quality Management – First in Quality

B. Braun Medical AG

Melsungen · Hybrid €36k – €60k/yr 1mo ago

About the role

About

Do you enjoy connecting complex data across systems? Do you believe that data without action is wasted potential? Do you think new outcomes require new ways of thinking?

In this role, you will help shape the future of medical technology at a leading German medical device manufacturer-ensuring world-class quality, regulatory confidence, and patient safety on a global scale.

This is not a role for passive analysis. It is for people who challenge assumptions, turn insights into direction, and want their work to measurably improve lives.

If you want to be part of real change-rather than observe it-this is your moment.

Responsibilities

Build a lifecycle "single source of truth" for AIS quality

  • Define and maintain a lifecycle-oriented data model that consolidates quality-relevant information across the entire product lifecycle
  • Connect and harmonize data from key functional systems such as SAP C3, Service tools, JIRA, MES and rework data to enable consistent reporting and end-to-end traceability
  • Establish and maintain data governance standards, including definitions, ownership, and quality checks, to ensure accuracy and reliability

Deliver a centralized dashboard and recurring reporting

  • Implement and continuously enhance a centralized dashboard providing visibility across Operations, Service and R&D, enabling proactive decision-making
  • Prepare regular reporting and transparent progress updates for leadership and key stakeholders
  • Translate raw data into actionable insights related to core KPIs-such as complaint trends, work orders, or cost of non-quality-to support preventive quality measures

Enable analytics that shift the organization from reacting to prevention

  • Perform deep-dive analyses to identify root causes, trend patterns and early warning indicators that support preventive action planning
  • Contribute to predictive and proactive analytics initiatives aligned with the digital PLM vision (e.g., quality prediction, lifecycle feedback loops)
  • Communicate insights clearly and ensure follow-up actions are owned and executed by responsible stakeholders

Drive benchmarking and best-practice identification

  • Support internal and external lifecycle benchmarking efforts to capture best practices and uncover improvement opportunities
  • Help define mandatory data sources and identify opportunities for AI-supported analysis during the diagnostic and concept phases of the program

Promote cross-functional enablement and adoption

  • Collaborate closely with Operations, Service, R&D and Quality teams to improve data capture practices and reduce manual, ad-hoc data handling
  • Contribute to strengthening transparency, collaboration and data-driven decision-making across the organization

Required Qualifications

  • Degree in Data Analytics, Industrial Engineering, Quality Engineering, Informatics, Computer Science or a similar field, or equivalent professional experience
  • Proven experience in building analytics-ready datasets using ETL, data-warehouse models (star/snowflake) or central data-lake structures, including data quality checks and full traceability
  • Strong ability to translate business questions into metrics, data pipelines and actionable insights, combined with clear stakeholder-oriented communication

Preferred Qualifications

  • Advanced SQL proficiency and hands-on experience with Python for data processing and analytics in a modern data ecosystem (ideally MS SQL, Azure Data Lake, Databricks)
  • Experience working with Power BI for semantic modeling, dashboarding and interactive reporting
  • Exposure to digital PLM or digital-thread concepts, including traceability across PLM-MES-ERP-QMS and feedback loops throughout the lifecycle
  • Understanding of regulated industries, especially medical devices, and familiarity with the relevance of traceability and compliance (e.g., EU MDR, FDA, ISO 13485)

Skills & Competencies

  • Analytical rigor: ability to structure ambiguous problems, identify patterns and quantify impact
  • Data-quality mindset: focus on accuracy, reliability, standardization and reducing manual error sources
  • Systems thinking: ability to connect product, process, service and operational data into a coherent, lifecycle-driven view
  • Clear communication: ability to translate insights into sound decision support under operational and time pressure

Benefits

  • Mobility options, e.g., the B. Braun job ticket or job bike
  • Services to support work & family, e.g., holiday childcare
  • Flexible working hours such as flexitime and working from home
  • Employee discounts
  • Various work models, e.g., job sharing/part-time

B. Braun Avitum AG | Tobias Franke | +495661715253

Salary

EUR 36000 - 60000 per year

Requirements

  • Degree in Data Analytics, Industrial Engineering, Quality Engineering, Informatics, Computer Science or a similar field, or equivalent professional experience
  • Proven experience in building analytics-ready datasets using ETL, data-warehouse models (star/snowflake) or central data-lake structures, including data quality checks and full traceability
  • Strong ability to translate business questions into metrics, data pipelines and actionable insights, combined with clear stakeholder-oriented communication

Responsibilities

  • Define and maintain a lifecycle-oriented data model that consolidates quality-relevant information across the entire product lifecycle
  • Connect and harmonize data from key functional systems such as SAP C3, Service tools, JIRA, MES and rework data to enable consistent reporting and end-to-end traceability
  • Establish and maintain data governance standards, including definitions, ownership, and quality checks, to ensure accuracy and reliability
  • Implement and continuously enhance a centralized dashboard providing visibility across Operations, Service and R&D, enabling proactive decision-making
  • Prepare regular reporting and transparent progress updates for leadership and key stakeholders
  • Translate raw data into actionable insights related to core KPIs-such as complaint trends, work orders, or cost of non-quality-to support preventive quality measures
  • Perform deep-dive analyses to identify root causes, trend patterns and early warning indicators that support preventive action planning
  • Contribute to predictive and proactive analytics initiatives aligned with the digital PLM vision (e.g., quality prediction, lifecycle feedback loops)
  • Communicate insights clearly and ensure follow-up actions are owned and executed by responsible stakeholders
  • Support internal and external lifecycle benchmarking efforts to capture best practices and uncover improvement opportunities
  • Help define mandatory data sources and identify opportunities for AI-supported analysis during the diagnostic and concept phases of the program
  • Collaborate closely with Operations, Service, R&D and Quality teams to improve data capture practices and reduce manual, ad-hoc data handling
  • Contribute to strengthening transparency, collaboration and data-driven decision-making across the organization

Benefits

mobility optionsholiday childcareflexible working hoursworking from homeemployee discountsjob sharingpart-time

Skills

Azure Data LakeDatabricksETLJIRAMS SQLMESPower BIPythonSAP C3SQL

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