- 🧠 Focus: Designing distributed data architectures, optimize ETL/ELT pipelines, and scaling AI infrastructure.
- 🔭 Currently engineering: Production-grade data workflows, market surveillance platform architectures, and open-source observability tools.
- 🌱 Deep Diving: Real-time streaming patterns, data lakehouse architectures, and LLM orchestration scale.
- 💬 Ask me about: PySpark optimization, SQL tuning, Snowflake warehousing, Docker orchestration, and why data quality matters.
- 🌐 Portfolio: prajeeshchavan.vercel.app
| 🚧 System / Product | 🔎 Architecture & Impact | ⚙️ Core Stack |
|---|---|---|
| Market Surveillance Platform | Contributed to a high-throughput financial data platform monitoring market anomalies with precise latency control. | PySpark, SQL, Databricks, PostgreSQL |
| OpenLLM Monitor | Open-source developer tool & telemetry dashboard built to track LLM execution metrics, tokens, latency, cost, and structural errors at scale. | React, Node.js, Express, TS |
| Placement Care / EventSphere | Full-stack robust enterprise management platforms featuring role-based access control, complex query indexing, and automated data updates. | MERN Stack, React Native |
“Optimize the pipeline, secure the infrastructure, and build what scales.”
— Prajeesh Chavan ⚙️