Arshta K.

Aws Data Engineer @DHL

CA

Building and maintaining ‘big data’ data pipelines, architectures, and data sets like DHL supply chain and transport data analytics datasets• Engineered scalable data pipelines using AWS Glue, AWS Lambda, and Amazon S3 to process and manage large-scale logistics and shipment data, enhancing operational insights and tracking across the global supply chain• Migrated legacy data systems to Amazon Redshift, optimizing data warehousing for real-time and historical analysis of logistics performance, leading to a 35% improvement in query performance and 40% reduction in operational costs• Designed and implemented AWS Kinesis and AWS Data Firehose streaming solutions to support real-time tracking and monitoring of shipments, reducing time to decision-making and improving customer satisfaction by providing live updates on delivery status• Developed and optimized data storage solutions using Amazon S3, and Amazon RDS to support dynamic supply chain demands, ensuring fast data retrieval and reliability for business-critical applications• Leveraged Amazon Athena for serverless data querying, enabling self-service analytics for logistics managers and improving data access without the overhead of managing traditional infrastructure• Implemented secure data access policies with AWS IAM, ensuring compliance with privacy standards and regulations such as GDPR, while enabling smooth data sharing across teams in a distributed, global environment• Designed and orchestrated complex workflows with AWS Step Functions, streamlining multi-step data processing tasks and minimizing downtime in data operations, contributing to better on-time delivery metrics• Utilized Apache Spark and PySpark for data transformation tasks, optimizing ETL pipelines to handle high volumes of operational data, improving system performance by 25%