Data Engineering student at STI (2025–2027) with a background in operations and team leadership. I build ETL pipelines, data platforms and medallion architectures with a focus on data integrity, automation and scalability.

Languages: Python (Pandas, OOP) · SQL (Advanced, CTEs)
Databases: PostgreSQL · DuckDB
Platforms & Tools: Databricks · PySpark · Delta Live Tables · Apache Kafka · Docker · FastAPI · Git
Modeling: ER-modeling · 3NF Normalization · Dimensional modeling
BI: PowerBI · Streamlit · Evidence.dev

End-to-end medallion pipeline on Databricks for 7.4M ultra marathon results (1798–2022).

• Streaming ingestion via Delta Live Tables into bronze
• 20+ silver transformations: unit standardization, date parsing, performance normalization, deduplication
• Dimensional model in gold: fct_results, dim_athlete, dim_event + analytical views
• Genie space for ad hoc queries with manual verification notebook
• Databricks dashboard built on gold views

End-to-end data pipeline with Kafka Producer/Consumer for async streaming from Spoonacular API into PostgreSQL (staging → curated). Cache-first strategy to minimize external API calls. ETL with Pydantic validation, NaN-handling and fuzzy ingredient matching. Exposed via FastAPI with search, history and query statistics endpoints. Scrum Master in a team of 5.

REST API ingestion of stock data stored as JSONB in PostgreSQL. ELT pipeline with Pandas for cleaning, validation and outlier detection. Flagging and rejection logic for data quality. Credentials via .env and containerized with Docker.

15 years as Team Leader at Citymail Sweden AB — responsible for process optimization, flow management and daily KPI delivery across teams of 6–10 people. That background makes me take reliability and edge cases seriously.

More projects and course work under my repositories.

• LinkedIn: linkedin
• Email: rickardgarnau@gmail.com
• Location: Stockholm

Seeking LIA internship. Open to data engineering roles.