Data Engineer | Scalable Big Data and Cloud Technologies Leveraging Solution Highly experienced data architect and optimizer with over 2 years of experience in designing and optimizing data pipelines using AWS, Spark, and Snowflake. In every single project I have been involved in, I have managed to increase retrieval speed by a minimum of 25% with the process efficiency improved by 20% or more. Summarily, I led a range of activities for the betterment of data quality at Trepp: error reductions by 30%, improvement in the accuracy of data through AWS Glue pipelines, and the development of dynamic dashboards in AWS QuickSight. These can transform raw data into insights that underpin strategic decision-making. I was responsible for leading ETL pipeline development and real-time data analytics platforms at Coditas. I reduced data processing time by 40%. Automated ETL scheduling and monitoring by using AWS Lambda to guarantee smoothness and reliability inside the systems. I am excited about advanced techniques in data engineering that empower effective solutions and enjoy working in an agile environment where innovation and efficiency are key. Core competencies: Big Data Tools: AWS, Spark, Snowflake, Databricks, Hadoop. Designing of Data Pipeline, ETL, SQL Optimization. Real-time Analytics & Dashboards: AWS QuickSight, Tableau, Power BI. Python, PySpark, Scala, SQL. Cloud Data Solutions, Data Warehousing, Automation: AWS Lambda, Step Functions. Feel free to connect if you need a Data Engineer who can drive success in your next project.