About

Ambar Raghuvanshi is a highly skilled software professional with expertise in AWS, Python, Spark, Hadoop, and real-time data pipelines. With 5.78 years of relevant experience, he has a good knowledge of creating large-scale machine learning training and real-time inferential pipelines. Currently, Ambar is working as a Senior Data Engineer at Zalando Payments, where he is creating large-scale ML pipelines for fraud detection in payments during order placement. He is using XGBoost as a fraud detection model, Sagemaker as an ML platform, Databricks on AWS for large-scale ML data preparation, and Cloudformation on zFlow as IaC. Before joining Zalando, Ambar worked as a Data Engineer I at Amazon, where he created large-scale real-time pipelines for Alexa Data Services to monitor and analyze the progress of manual annotation of audio data. He used lambda as the real-time processor, SNS as the pub-sub service, SQS as the wait queue, RDS as the target database, Redshift as the large-scale analytics platform, AWS Managed Airflow as the batch processing orchestrator, and CloudFormation as IaC. He has also worked as a Business Technology Solutions Associate at ZS Associates, where he developed flask APIs for DQM for inserts and updates of HCP and HCO on Reltio. Ambar has a Bachelor's Degree in Computer Engineering from Shri G S Institute of Technology & Science. He has also completed his Senior School Certificate from Kiddy's Corner School and Indian Certificate of Secondary Education from Wendy School Junior College. He is proficient in various technologies, including AWS, ML, Spark, Python, XGBoost, Hadoop, Sagemaker, Databricks, Apache Airflow, Typescript, SQL, Jupyter, Django, ETL, Flask, and Apache Hive. Ambar is open to exciting opportunities and can be contacted at ambarraghuvanshi@live.com. He has also provided a referral link to Zalando for interested candidates.