Junior Data Engineer focused on building reliable end-to-end data pipelines and analytics workflows using Python, SQL, PostgreSQL, dbt, Apache Airflow, Databricks, Docker and Azure. I recently completed the HackYourFuture Data Engineering programme, where I worked on production-style data projects and a team final project. I'm particularly interested in data platforms, analytics engineering and cloud-based data systems.
- Turning my HackYourFuture final team project into a portfolio-ready data engineering project
- Reworking a real-estate data platform with a stronger data engineering and analytics architecture
- Building ETL/ELT pipelines with Python, SQL, dbt and Apache Airflow
- Improving data modelling, data quality and data-contract practices
- Expanding my experience with Databricks and cloud-based data platforms
- Python
- SQL
- Jinja
- PostgreSQL
- dbt
- Apache Airflow
- Databricks
- Pandas
- REST APIs
- ETL / ELT
- Data Modelling
- Data Quality Testing
- Pydantic
- Azure
- Azure Blob Storage
- Azure Database for PostgreSQL
- Docker
- Git
- GitHub
- GitHub Actions
- Streamlit
- Metabase
End-to-end event data platform developed as part of a cross-functional team project.
My contribution: API research and data contract design, dbt transformations in Databricks, Airflow workflows, event-price enrichment, venue enrichment and data-platform monitoring.
Stack: Python • SQL • dbt • Databricks • Apache Airflow • Streamlit
Data engineering and analytics platform for exploring the Dutch housing market using public data sources.
Stack: Python • PostgreSQL • dbt • Apache Airflow • Azure • Docker
Analytics engineering project with dbt transformations, analytical marts and interactive dashboards.
Stack: Python • SQL • dbt • PostgreSQL • Metabase • Streamlit