I design and implement end-to-end data solutions using Python, SQL, and cloud technologies — transforming raw data into reliable, decision-ready insights.
I am a Data Engineer with a strong foundation in IT and over 20 years of experience working with complex systems.
Recently, I specialized in building modern data pipelines and platforms using tools such as Python, SQL, DuckDB, and cloud technologies (GCP, AWS, Azure).
My work focuses on designing scalable data architectures, ensuring data quality, and delivering reliable datasets for analytics and decision-making.
I combine practical engineering skills with a problem-solving mindset, bringing structure and efficiency to complex data environments.
I am fluent in German, English, and Portuguese and open to international remote opportunities.
Processes 22M+ telemetry records from the Dutch national railway network using a modern data stack. Features a "Black Hole Audit" that identified 748K+ ghost stops, and a 220% delay penalty model for platform changes. Pipeline optimized via BigQuery BI Engine for sub-second Looker Studio performance.
Designed a medallion architecture (Bronze/Silver/Gold) for multi-source retail data processing. Resolved critical data quality issues including inconsistent categories, missing data, and date parsing errors. Recovered large portions of unusable historical data and built analytical datasets supporting revenue and operational decision-making. Applied similarity models and forecasting techniques for business insights.
Implementation and customization of Customer Relationship Management systems, improving business processes and customer service efficiency.
Successfully managed and delivered complex IT projects, ensuring timely completion and optimal resource utilization.
Interactive BI dashboards built with Power BI, providing real-time insights and data visualization for decision-making.
Open to international remote opportunities in Data Engineering. Reach out via the form, or connect on LinkedIn or GitHub.