I'm a Business Informatics student specializing in Data Engineering & AI Application Development, passionate about building robust, scalable data infrastructure and AI-driven applications that power intelligent decision-making.
My interests span the entire data lifecycle - from ingesting and processing of raw data to building machine learning & AI pipelines that deliver real-time insights. I really like solving data challenges and optimizing data & AI applications for performance and reliability.
I'm currently focused on improving my data understanding as well as technical skillset like Python, SQL (dbt) & Databricks.
Building modular SQL transformations for data warehousing
Data transformation & cleaning using Spark
Designing data models optimized for analytics and BI
Featured Work
Real-world projects demonstrating end-to-end data engineering skills
Serverless ELT pipeline for SaaS analytics with BigQuery and Looker Studio
Chat-based analytics tool using GPT-4o for SQL generation with secure execution
Centralized monitoring and alerting system for tracking data pipeline health and performance
An end-to-end, orchestrated ELT pipeline for F1 historical data deployed with Docker
Digital checklist system replacing paper-based task tracking for daily shift operations
Strategic AI consulting and training for a real estate company to integrate AI into internal workflows
A comprehensive quiz for lead generation targeted at potential customers that sell their properties privately
A web-based dashboard that tracks the performance and answers of the quiz, grouped by customers
Integrated and set up a CRM system for managing customer relationships and sales processes for 10+ real estate agents
Technical Stack
These are the tools & technologies I've worked with until now
During my studies, I've also gained some experience through certifications & online courses.

DataCamp

DataCamp

DataCamp
My Posts on Medium
Technical articles about data engineering, analytics, and modern data stack
Exploring the evolution of data architecture patterns and how modern lakehouse solutions bridge the gap between traditional data warehouses and data lakes for better analytics performance.
Deep dive into graph databases and knowledge graphs, their applications in recommendation systems, and how they're transforming advanced analytics in modern data architectures.