Amrutha Varshini Bethala

Executed data extraction and integration from diverse sources into Azure Data Lake using ETL pipelines.
Migrated data from on-premises systems to Azure utilizing Azure Data Factory for seamless transitions.
Developed and tuned ADF copy activities and transformations with Mapping Data Flows for enhanced efficiency.
Converted data into optimal formats, ensuring effective reads, memory usage, and calculated key metrics.
Implemented Spark in Databricks with Python to improve processing speed using Data Frames and Spark SQL API.
Enhanced performance of existing algorithms in Hadoop by employing Spark Context, Spark SQL, and Data Frames.
Created dynamic pipelines via parameterization and control tables to meet project requirements effectively.
Applied business logic with PySpark in Databricks and ADF, delivering tailored data solutions.

• Monitored open and unmatched buy and sell trades to ensure accuracy in NAV calculations.
  Conducted weekly variance analysis on market value, bidding price, and base unit cost.
  Calculated gross return and net return of each mutual fund using NAV data.
  Coordinated with teams to resolve issues in current reports effectively.
  Dispatched client deliverables according to service level agreements.
  Calculated share/par value and base market value for sensitive client reports across multiple funds.
  Processed current reports by sorting and cleaning data to enhance reliability.
  Prepared monthly management and administrative expenses, analyzing reputational risk and ensuring accurate expenditure reporting.