
Data EngineeringApplied academic project2026
Spark, Kafka and Airflow data platform
Processes batch and real-time data with Spark, Kafka and Airflow and organises it into layers of increasing quality (Medallion architecture) on Delta Lake.
- Apache Spark4.0.1
- Delta Lake4.0.0
- Apache Kafka4.1.1
- Apache Airflow3.0.6
- MinIOS3 local
- SQL Server2022
- DockerCompose
- LicenseMIT
Problem
Maintain a living metadata catalogue by combining structured, semi-structured and real-time event sources.
Architecture
SQL Server, CSV and Kafka feed Spark jobs that publish Bronze, Silver and Gold layers on Delta Lake and MinIO. Airflow orchestrates the batch flows.
Data flow
Sources → batch or streaming ingestion → Spark → Medallion Delta Lake → verifiable Gold previews.
Results
3
Ingestion patterns
Incremental SQL batch, CSV batch and Kafka streaming
View source3
Data layers
Bronze, Silver and Gold in every pipeline
View sourceContribution and authorship
- Use-case and Medallion architecture design
- Implementation of Spark jobs and Airflow DAGs
- Reproducible integration of Kafka, SQL Server, MinIO and Delta Lake
Alonso Marcos Muñoz · Author and developer
Evidence
Limitations
- • Reproducible local environment with demo data, not an enterprise production platform
- • Included credentials are local development values only
Stack
https://github.com/alonsomarcosm99/spark-kafka-airflow-data-platform