
Krishna Karthik Chava
Engineering / Architecture
About Krishna Karthik Chava:
I worked as a Full-Time Data Engineer at Zoho Corporation, where I was part of Zlabs, Zoho’s internal analytics team. My role involved analyzing and comparing over 250+ Zoho products globally, providing insights that significantly improved the client-developer requirement phase. These optimizations contributed to exponential growth in profits by aligning product development with customer needs.
During my internship at Zoho, I worked on agriculture and farming analytics, developing data-driven solutions to enhance crop productivity and farm management. By leveraging data pipelines and visualization tools, I helped streamline decision-making for sustainable farming initiatives.
Experience
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I worked as a Full-Time Data Engineer at Zoho Corporation, where I was part of Zlabs, Zoho’s internal analytics team. My role involved analyzing and comparing over 250+ Zoho products globally, providing insights that significantly improved the client-developer requirement phase. These optimizations contributed to exponential growth in profits by aligning product development with customer needs.
During my internship at Zoho, I worked on agriculture and farming analytics, developing data-driven solutions to enhance crop productivity and farm management. By leveraging data pipelines and visualization tools, I helped streamline decision-making for sustainable farming initiatives.
Education
Data Engineer (Graduate Research Assistant) - Portland State University JAN 2025 - JUN 2025, Portland, OR, USA
- Built a real-time data pipeline using Google Cloud Pub/Sub, Python, and PostgreSQL to ingest and validate >17GB of TriMet GPS and stop event data.
- Developed custom APIs (HTML and JSON), performed data quality checks, calculated speed metrics, and stored results in structured PostgreSQL tables.
- Automated data streaming and server uptime with systemd services, while supporting students and providing feedback to enhance their understanding and project outcomes using clean, accessible transit datasets.
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