About Me
Welcome to my webpage! Here's a glimpse into my career path - in my current role I've discovered a growing excitement for Data Engineering and Warehousing. This complements my academic background in Data Science, offering me a big picture of the field. Being active in both areas allows me to understand the interconnectedness and vital role they play in each others success. It's been an enlightening transition, where I've also mastered the Data Vault technique, earning my certification. This site displays my ongoing journey, a balance between the exciting field of Data Science and the crucial framework of Data Warehousing.
Core Skills
Data Engineering
AI Engineering
Cloud Computing
Agile Project Management
Professional Experience
AI/Data Engineer at GIZ in Bonn (2024–Present)
I work with Azure AI Foundry, deploying and managing agents and prompt flows to automate enterprise workflows. I build production data pipelines from ingestion (web scrapers, connectors) through transformation using Medallion architecture and Data Vault principles for historization, all powered by PySpark and Delta Lake tables in Azure Fabric. I develop automated evaluation pipelines and judge-AIs for evaluating model performance, conduct performance benchmarking and optimization of AI models in production, and build advanced reporting and data models to bridge analytics and engineering capabilities.
Hospitation in Lima, Peru (2025)
During my three-month on-site assignment in Lima, I supported international cooperation projects by working with local teams on data initiatives. I built POCs and pilots with local partners, including agentic AI systems that can autonomously access various information flows. I contributed to reporting, process automation, and intercultural knowledge exchange, gaining valuable exposure to development cooperation in practice.
Junior Data Specialist at GIZ in Bonn (2022–2023)
In my role as a Junior Data Specialist, I implemented and programmed in Azure Synapse while innovating with machine learning to improve data efficiency. I brought together the worlds of Data Science and Data Engineering, refining our approach to data and ensuring it was not only managed but also intelligently transformed into valuable insights. By integrating machine learning with scalable Data Vault techniques, I advanced our systems toward smart automation and predictive capabilities, making our data strategies both time-efficient and future-ready.
Dual Student at GIZ in Bonn and Frankfurt am Main (2019–2022)
My dual studies at GIZ combined academic learning with substantial professional experience across multiple departments. I applied university principles in real-world projects, contributed to the workers' council, and developed a strong foundation in digital operations and international project management, gaining hands-on experience in development cooperation.
Education
Master’s Degree
University of Cologne — MSc. Business Analytics & Econometrics (2022–2024)
Master’s thesis: “Innovative Cloud Data Warehousing: Integrating LLMs for Automated Document Processing and Evaluation” — grade 1.0 (highest distinction). Overall degree grade: 1.7.
Focus: AI-powered document processing, RAG, data warehousing on Azure Fabric.
Bachelor’s Degree
Trier University of Applied Sciences — BSc. Information Systems (Dual, 2019–2022)
Overall degree grade: 1.8. Key modules: Machine Learning, Advanced Business Analytics, Data Mining.
Exchange Semester
University of Worcester (England) — Exchange Program (2021–2022)
Resume
View My ResumeCertifications
Projects
This section is a work in progress, where I'll be showcasing projects I've tackled and new adventures I'm embarking on in the world of data and machine learning. Stay tuned for updates and insights into my hands-on experiences!
The Portfolio Website Challenge: A journey into web development
Curious about new technologies, I took on a two-day challenge to build this particular portfolio website. It was a practical jump into web development - a field new to me - with the aim of creating a space that represented my professional journey. I started with the basics of HTML, CSS and JavaScript. Then I moved on to deployment, where Render was suitable for a good and free deployment of my final repository. Now all I needed was a domain to make myself visible in Google searches. I found a cheap product from IONOS and configured my web domain for 2€. The result was a cheap and efficient product to bring this site to life. This project, built from scratch, demonstrates my adaptability and willingness to learn directly in the medium I am exploring.
Exploring Genre and Success Classification through Song Lyrics using DistilBERT: A Fun NLP Venture
The Song Analysis App was a key university project where we ventured into the fusion of artificial intelligence and music. Harnessing the power of Large Language Models (LLMs) such as BERT, our team developed a Streamlit-based dashboard capable of deciphering the complexities of song lyrics. In a University project with fellow data science students, we developed a solution that not only categorises song genres, but also predicts their release years and measures their popularity. More than an academic exercise, this project was an exploratory odyssey into the rhythmic heart of music, uncovering hidden patterns and trends with the precision of machine learning. For an in-depth look at our group's journey and the technical intricacies of our work, please read the detailed paper linked below.
Data Insights in IoT for Pets
In this capstone project, I delved deep into machine learning to analyze IoT data from dog trackers. Working with two other students over three months, we aimed to understand pet owner behaviors and enhance device functionality. Our close collaboration with the business taught us about managing requirements and the importance of continuous improvement. We tackled challenges in data processing and interpretation, applying complex ML algorithms for valuable insights.
