Speaker: Dheeraj Rampally

Senior Software Engineer @Paypal

Dheeraj has 5 plus years of experience in building high scalable big data applications. Initially he worked at Yahoo where he contributed to Supply forecasting, Ad-serving by building Data Pipelines in Apache Pig, Spark and Oozie. He also has hands on experience in Document based stores like Mongo DB and Columnar stores like Druid. Currently he is working as a senior software engineer at Paypal where he is the core contributor to the Data Catalog which constitutes building highly scalable low latency applications in Java and Data discovery in Scala. Additionally, he works on the Unified data api in Scala on Spark Compute. He is also a contributor of several core features in PayPal’s Gimel Elastic Search API.

Find Dheeraj Rampally at

Proposed Tracks

  • Real-World Data Engineering

    Showcasing DataEng tech and highlighting the strengths of each in real-world applications.

  • Deep Learning Applications & Practices

    Deep learning lessons using Tensorflow, Keras, PyTorch, Caffe across machine translation, computer vision.

  • AI Meets the Physical World

    The track where AI touches the physical world, think drones, ROS, NVidea, TPU and more.

  • Data Architectures You've Always Wondered About

    How did they do that? Real-time predictive pipelines at places like Uber, Self-Driving Cars at Google, Robotic Warehouses from Ocado in the UK, are all possible examples.

  • Applied ML for Software

    Practical machine learning inside the data centers and on software engineering teams.

  • Time Series Patterns & Practices

    Stocks, ad tech/real-time bidding, and anomaly detection. Patterns and practices for more effective Time Series work.