Summary
Prakhar Srivastava is a Senior Data Engineer based in Amsterdam with a decade of experience building large-scale data and ML pipelines across cloud platforms like AWS and GCP. He combines deep production expertise in Hive, Airflow, Trino, Argo and Kubernetes with hands-on skills in Python, Go, Scala and Java to deliver reliable, observable data systems using Fluentd, Prometheus, Grafana and Kibana. At Atlan and subsequent roles he scaled ML workflows over multi-terabyte datasets—applying models from KNN and SVM to ResNet-50 U-Net on satellite imagery—and implemented GIS-centric feature engineering with GeoPandas and GDAL. Equally comfortable architecting CI/CD and GitOps practices as he is prototyping novel models, he brings a pragmatic blend of data engineering rigor and research-minded experimentation. Notably, his work spans both real-time logging/analytics pipelines and large-batch ML at production scale, reflecting a rare full-stack data engineering profile.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Technology (B.Tech.) Computer Science, Bachelor of Technology (B.Tech.) Computer Science at Guru Gobind Singh Indraprastha University
English, Hindi