Engineer with 4+ years’ experience in automotive manufacturing (Skoda-VW & Mercedes Benz), specializing in quality systems, root cause analysis, and lean implementation. Proven ability to lead problem-solving initiatives (8D, DMAIC, PDCA) and support Quality Management Systems. Adept at data analysis and dashboard automation using Power BI and Databricks. Passionate about driving operational excellence in electric vehicle manufacturing environments.
As part of the Global Production Engineering program at TU Berlin, successfully completed my master’s thesis in collaboration with Mercedes-Benz AG at Werk Bremen. The thesis focused on the optimization, integration, and visualization of Screwdriving production data from assembly halls. The objective was to transform raw, unstructured manufacturing data into a centralized, real-time monitoring system using Databricks for data processing and Power BI for interactive visualization.
Designed and implemented end-to-end data pipelines in Databricks (SQL and Python). The output was a modular Power BI dashboard system, enabling quality engineers, production managers, shift leaders, and controllers to analyze non-conformities (NIOs). This tool enabled early defect detection, root cause analysis, and faster decision-making, leading to a 41% improvement in data transparency and a 17% reduction in quality deviations. It is also indented to further expand to all Mercedes Benz plants across Germany and worldwide.