Parul Agrawal

About Parul Agrawal

8+ years of experience in Python, Matillion, Snowflake, Power BI, SQL, Azure, AWS, RESTful API, PySpark, SparkSQL, AML, ML (Basics), Big Data,Data bricks, EXCEL, HTML, CSS, Oracle EBSs.1. Orchestrated a successful migration of the data warehouse architecture, resulting in removal of Redshift storage cost and 40% reduction in data processing time and enabling real-time analytics for the cross functional teams. Developed PBI dashboard to track Performance of migration.2. Achieved an astounding 88% reduction in data warehouse load time by implementing advanced optimization techniques, slashing processing time from 2 hours to an impressive 15 minutes.3. Designed, Developed and Implemented an end to end Automation pipeline using Matillion, Snowflake, AWS S3 and Sharepoint to Perform Data Correction and Generation of Monthly Reports for the Accounting Team\'s Month-End Reconciliation.This pipeline has significantly reduced days of manual effort down to just an hour. Established a Matillion Pipeline to automate the entire process of generating CSV and Excel files from Snowflake to Amazon S3 and subsequently uploading them to SharePoint.4. Developed highly scalable Python code using Microsoft Graph APIs for uploading CSV and Excel files from S3 to SharePoint, which has proven valuable for other projects.5. Designed and developed many SSRS and Power Bi dashboards for customers and stakeholders and subscribed them to send over slack and outlook.6. Enhanced and optimized Full load pipelines to Incremental or Batch load resulting in reduction of compute power by 45%.7. Worked with cross-functional teams to integrate data from multiple sources, both structured and unstructured, to create a unified view for reporting and analytics.8. Implemented data quality checks and validation mechanisms at various stages of the ELT pipeline to identify and rectify data anomalies and inconsistencies.9. Monitor ETL processes, troubleshoot and resolve issues in a timely manner. Implement error handling, logging, and alert mechanisms to ensure robust and reliable data pipelines.10. On Premise to Cloud Migration- Build an ETL in Big Data capabilities with PowerBI dashboard integration to track and visualize the content of files placed in local machine for Regulatory Reporting using Azure HDInsight, Power BI, Python, Big Data technologies like Hive, PySpark, SQOOP. Azure Data Bricks was used to transform data in staging hive table to final hive table using PySpark. Automated the complete process using Shell script and python script.

Experience

1. Data Engineer

   Microsoft

   Mar 2024 — Present · Noida, IN

Education

• Maulana Azad National Institute of Technology

  Bachelor of Technology (B.Tech.), Material Science and Metallurgical Engineering

  2011 — 2015

• Maharishi Vidya Mandir

  Mathematics

  1997 — 2010

Skills

• Bi Publisher
• Sql
• Customer Service
• Dbms
• Oracle Report Builder
• Microsoft Word
• Management
• Microsoft Office
• Pl/Sql
• Microsoft Excel
• Powerpoint
• Plsql