Venkata Gowtham Yadla

I am a data engineer and automation specialist with a strong background in building robust, scalable solutions for data extraction, transformation, and analysis. My work bridges the intersection of software engineering and data science, with a particular focus on web automation, database integration, and predictive analytics in domains such as energy and infrastructure.

My expertise lies in developing end-to-end data workflows using Python, leveraging libraries such as Selenium for intelligent web scraping and OCR tools for extracting information from dynamic web content, including CAPTCHA-secured interfaces. This allows me to collect high-value data from complex or protected sources and make it usable for downstream analytics.

On the backend, I work extensively with SQL Server and PostgreSQL databases, ensuring seamless integration of structured data into relational models. I often design scripts that not only fetch and clean data but also enrich it with metadata such as revision history, timestamps, and semantic tags, enabling smarter queries and analytics. Whether it’s ingesting real-time forecasts from APIs or transforming legacy data for historical analysis, my workflows are built for accuracy, traceability, and efficiency.

I also contribute to machine learning workflows by preparing feature-rich datasets, tracking performance metrics, and supporting forecasting models — especially in applications like energy demand prediction. I pay careful attention to versioning, data validation, and reproducibility, all of which are critical for building trust in automated decision-making systems.

I value clean, maintainable code and often follow best practices in modularity and error handling. Whether I’m working on a browser automation pipeline or designing an ETL process, I strive to make solutions that are easy to maintain and scale.

Beyond my technical work, I enjoy exploring new technologies in OCR, image processing, and API design. I constantly seek better ways to streamline repetitive tasks and empower decision-making through data. I’m motivated by challenges that require both creativity and precision — especially those that sit at the boundary of software and data.

In short, I help systems talk to each other: scraping information where it's hidden, cleaning it where it's messy, storing it where it's useful, and analyzing it where it matters most.