Summary
Pranshu Shrivastava is a Tech Consultant (AI) and data engineer with nine years of experience building reliable, analytics-ready pipelines on AWS and deploying production workflows with Airflow, Docker, EKS and GitHub Actions. He specializes in ETL/ELT from transactional stores and APIs into columnar warehouses (Redshift) with incremental loads, data quality gates and Kimball-style modeling to enable self-service BI via Power BI/Tableau. His background spans Deloitte enterprise projects, Kafka→Spark streaming, and deep learning research, giving him a rare blend of enterprise data engineering and academic ML rigor. Currently focused on strengthening AWS Data Engineer and Terraform skills, he also documents systems through runbooks and data dictionaries to make complex pipelines operable by product and analytics teams. Based in Gurugram, he pairs hands-on Python/PySpark implementation with stakeholder-facing KPI clarity, and has shifted from aspiring ML roles on GitHub to demonstrable production data systems in recent positions.
9 years of coding experience
5 years of employment as a software developer
Bachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at Vellore Institute of Technology
Master's degree, Big Data & Business Analytics, Master's degree, Big Data & Business Analytics at SRH University
English, German