Tobias Kapp

I help companies build stable, scalable cloud data platforms and sustainably improve existing ETL pipelines in cloud technologies such as Snowflake, Azure Data Factory, and Databricks. My focus is on noticeably increasing data quality, performance, and maintainability – not just solving problems short-term.

As a Senior Cloud Data Engineer, I bring over six years of project experience in the conception, implementation, and optimization of data engineering solutions. I work at the interface between business departments and IT, translating business requirements into clean data models, robust ETL pipelines, and production-ready architectures.

What sets me apart is my systemic view:

I analyze data landscapes holistically – from source through transformations to reporting – and identify structural weaknesses that lead to instability or high maintenance effort in the long run. Based on this, I develop pragmatic, actionable solutions that can be integrated into existing system landscapes.

Typical project types and results:

- Building and optimizing ETL pipelines in Azure and Snowflake

- Performance tuning and refactoring of SQL

- Improving data quality and error robustness in production data warehouses

- Architecture reviews including concrete recommendations for action

- Supporting teams through workshops, documentation, and knowledge transfer

Additionally, I work on LLM and RAG-based use cases, particularly in the evaluation and prototypical implementation of AI-powered solutions on existing data platforms. My aim is to create realistic added value.

My goal is to help companies establish viable data platforms that remain understandable, stable, and extensible even with growing complexity. I work in a structured, transparent manner with clear communication to technical and business stakeholders.