I’m Xiaolong Song, a data engineer based in the Netherlands.
I build data platforms and apply LLMs in production. Recent work includes PySpark pipelines processing 120M+ rows per day, lakehouse architectures on GCP and Microsoft Fabric (Delta Lake, BigQuery, dbt, Airflow), and AI engineering: LLM cost engineering, prompt caching, and coding-agent workflows.
Before data, I spent four years as an infrastructure engineer, then moved into this field through an MSc in Statistics and Data Science at KU Leuven. That detour shaped how I work: data problems are engineering problems, and they deserve versioning, tests, and honest trade-off analysis.
What I write about here:
- Data engineering: pipelines, lakehouse patterns, orchestration, data testing
- AI engineering: LLM cost engineering, prompt caching, agentic workflows
- Fundamentals: occasional deep dives into the CS underneath the tools
Find me on GitHub and LinkedIn, or reach me at andrewsong93@gmail.com.