Madan Mohanan

I am a Data Engineer professional with over 8 years of industry experience in developing large-scale data processing and analytics, creating end-to-end data solutions. Graduated as Master's in Computer Science from Roosevelt University. Prior to which I was working as Data Engineer in Publicis Sapient building scalable ETL processes & data migrations to implement automated workflows to ingest, transform and load multiple sources into aggregated data on large-scale retail entities (>1TB daily).

Before joining Sapient I worked as Data Engineer/Data Analyst at DIATOZ Solutions, where I was focused on retail project to migrate on-premise databases to AWS environment leveraging on-demand services like Lambda, Glue and Step functions and generate reports and create dashboards for timely reports.

Over the course of my professional career, I have developed strong and varied expertise in techniques like PySpark, SQL, Terraform, Docker, Data Warehousing, Data Modeling, ETL pipelines, Project Management, Reporting, Big Data, Cloud Computing & Consulting. I'm dedicated to helping businesses leverage real-time updates, providing scalable end-to-end data solutions with passion in the rapidly evolving machine learning and deep learning fields.

My skillset is a blend of various tools and technologies, including but not limited to:

📍 Hadoop Ecosystem (HDFS, Hive, Sqoop, Hbase)

📍 Scala / Python

📍 SPARK (PySpark, Databricks)

📍 Snowflake

📍 SQL (SQL Server, Oracle, MySQL)

📍 Tableau, PowerBI

📍 Azure Cloud (ADF, ADLS/Blob, Synapse and other related services)

📍 AWS (Glue, Step functions, Lambda, RDS, SNS, S3, and other related services)

I am a Data Engineer professional with over 8 years of industry experience in developing large-scale data processing and analytics, creating end-to-end data solutions.

Experience in Publicis Sapient building scalable ETL processes & data migrations to implement automated workflows to ingest, transform and load multiple sources into aggregated data on large-scale retail entities (>1TB daily). Before joining Sapient I worked as Data Engineer/Data Analyst at DIATOZ Solutions, where I was focused on retail project to migrate on-premise databases to AWS environment leveraging on-demand services like Lambda, Glue and Step functions and generate reports and create dashboards for timely reports.

Over the course of my professional career, I have developed strong and varied expertise in techniques like PySpark, SQL, Terraform, Docker, Data Warehousing, Data Modeling, ETL pipelines, Project Management, Reporting, Big Data, Cloud Computing & Consulting. I'm dedicated to helping businesses leverage real-time updates, providing scalable end-to-end data solutions with passion in the rapidly evolving machine learning and deep learning fields.

Master's in Computer Science at Roosevelt University