Building reliable data systems at scale
I design and maintain modern data platforms using Python, SQL, Spark, orchestration, and cloud infrastructure.
PythonSparkAirflowKafkadbt
Philosophy
I believe that data systems should be boring, scalable, and self-documenting. Reliability isn't a feature; it's the foundation of every architectural decision.
Toolkit
Python, Spark, Airflow, Kafka, dbt, Snowflake, Kubernetes, AWS, GCP.
Workspace
MacBook Pro M3, VS Code, iTerm2, and Obsidian for knowledge management.
Learning
Currently deepening my understanding of Rust and its potential for high-performance data processing pipelines.
Status
Open for consulting
Projects
6+ Production pipelines