Python is often praised for simplicity, but criticized for low performance and scalability. Bodo is a new compute engine that brings supercomputing-like performance and scalability to native Python analytics code. Bodo automatically parallelizes Python/Pandas code allowing applications to scale to 10,000+ cores and petabytes of data without any rewrites into Scala, C++ or non-native APIs, making Python the best solution for challenging data engineering tasks like ETL, data prep, and featurization. This is made possible using a new just-in-time (JIT) inferential compiler technology that can automatically performs the optimizations that usually require efforts from world-class performance experts. We will discuss how this technology works, present examples and benchmarks and explain why it is orders of magnitude faster than alternatives such as Spark and Dask.