Turning raw data into pure power—this repository is a collection of my data engineering projects, where complex datasets are transformed into streamlined, actionable assets. From designing robust ETL pipelines to architecting scalable data infrastructures, these projects showcase the backbone of modern data solutions. Dive in to explore how messy, unstructured data becomes the fuel for analytics, machine learning, and beyond.
- Project 1: Developing Input Features for Personalized Marketing
- Developed input features for an ML model to enhance marketing strategy, focusing on transforming visitor log and user data into actionable metrics like views, user activity, and product interactions. This enables targeted advertisements and personalized offers to boost revenue and conversion rates.
In this repository, you'll find projects that reflect my passion for building data systems that are not just functional but also scalable, reliable, and efficient. These projects demonstrate my skills in data architecture, pipeline development, and workflow automation—key components in turning data into a strategic asset.
Feel free to explore the projects, review the code, and learn from the methodologies employed. Whether you're an aspiring data engineer or an experienced professional, there’s something here for you. If you find these projects insightful or helpful, don’t forget to star the repository!
For further discussions on potential collaborations or to gain deeper insights into my projects, please feel free to contact me via email at 3sripathi@gmail.com. Additionally, you can explore more of my in-depth analyses and observations on machine learning on my Medium blog or connect with me on LinkedIn.