I believe that data is the heartbeat of any operation—from a local warehouse to a global business. If there is input and output, there is a story to be told. My mission is to translate those stories into measurable value by involving all stakeholders; I believe we can drive impact together.
My expertise ranges from high-level Excel modeling, Looker, and BigQuery analytics to building multilingual NLP models. I specialize in bridging the gap between traditional business intelligence and emerging Web3 technologies, ensuring data drives measurable user value.
I am driven by the belief that technology should be a catalyst for positive change. I strive to contribute to any technology that pushes the boundaries of what is possible—transforming raw data into a force for innovation and social impact.
| Project | Area | Contribution & Key Impact |
|---|---|---|
| Web3 Intelligence | Decentralized Data | Enhanced Ethereum provider logic to streamline data indexing pipelines for DeFi analytics. |
| BigQuery Ecosystem | Data Engineering | Developed and shared optimized SQL scripts for processing multi-terabyte datasets, reducing latency. |
I focus on building end-to-end pipelines that ensure data drives measurable user value, moving from raw ingestion to production-ready insights.
- Scalable ETL & Integration: Architecting robust workflows that ingest unstructured JSON and relational data (PostgreSQL) into high-performance warehouses like BigQuery for enterprise-scale analysis.
- Predictive Research & Modeling: Transitioning complex EDA from Jupyter Notebooks (utilizing Pandas, Matplotlib, and Seaborn) into production-grade BigQuery ML and machine learning models.
- Mission-Driven Web3 & Sustainability: Bridging the gap between Web3 transparency and sustainability analytics, ensuring decentralized data leads to verifiable environmental impact.
BQ2PG | Data Interoperability Pipeline
- The Problem: Data often becomes siloed in cloud warehouses, making it difficult for localized applications to access.
- The Solution: A migration pipeline to sync data between Google BigQuery and PostgreSQL.
- Value: Enables businesses to leverage analytical power while maintaining operational agility.
datacleanx | Automated Data Integrity Engine
- The Problem: Manual cleaning is the biggest bottleneck in the data science lifecycle.
- The Solution: A toolkit to automate EDA and cleaning for JSON and CSV inputs.
- Value: Transforms messy data into analysis-ready assets, reducing preparation time by 60%.
chainguard | Web3 Data Security Research
- The Problem: Transparency in Web3 is only valuable if data is secure and verifiable.
- The Solution: Research-driven monitoring of on-chain data flows to ensure resilience.
- Value: Provides a framework for secure, mission-driven decentralized tech.
Open to remote global opportunities at the intersection of Product, Data, and Web3.