Karandeep Sahni Email & Phone Number

Project :- Mobile Performance• Designed and implemented data processing pipelines using Python and Apache Airflow to integrate mobile delivery data from Samsung Ads platform.• Leveraged AWS services (S3, EMR, Lambda, Athena) for efficient data storage and analysis of data in Parquet, JSON, and Avroformats.• Deprecated legacy systems, resulting in faster analysis and reporting capabilities for immediate actionable insights.• Optimized ETL pipelines and Spark transformations, achieving annual AWS cost savings of $1.5 million through efficient data processing and storage strategies.Project :- STAQ• Implemented ETL processes to process raw data from the data lake into the data warehouse within Hadoop Distributed File System (HDFS).• Handled critical 3rd Party billing reports in real-time, ensuring accurate and timely billing to customers.• Built real-time data streaming pipelines using Kafka and Spark Streaming, achieving a 97% accuracy rate in billing operations.• Enhanced ETL pipeline performance by integrating Snowflake with Apache Airflow, achieving significant efficiency gains in data processing.

• Implemented real-time data processing pipelines using PySpark and Kafka, enabling streaming analytics and real-time insights.• Designed and implemented scalable and efficient data pipelines using Apache Spark and Python, processing large volumes of data for analytics purposes.• Managed data infrastructure on AWS, including setting up and optimizing Amazon EMR clusters, S3 storage, and EC2 instances.

Mumbai, Maharashtra, India

• Assisted in developing and testing data pipelines using Hadoop and Apache Hive for processing structured and semi-structured data.• Optimized SQL queries and database performance, reducing query execution time by 30%.