I enjoy designing data pipelines that are simple, scalable, and easy to reason about.
I work at the intersection of data engineering and cloud platforms.
Most days, I am building pipelines, cleaning messy data, or learning how large systems behave at scale.
I like systems that are:
- predictable
- observable
- easy to maintain
Silence helps me focus. Clean logs make me happy.
- Streamlit based data apps connected to AWS S3
- Batch style pipelines using Python and SQL
- Exploring Azure Databricks, PySpark, Kafka for distributed data processing
- Data modeling for analytics workloads
- Spark internals and performance tuning
- Event-driven pipelines and message queues
- Writing clearer documentation for data systems