Prashansa Pralhad Chaudhary

 Skillfully developed and maintained an ETL framework using PySpark, which included daily runs, error handling, and logging, thereby enhancing
data processing efficiency.
 Pioneered the development of PySpark applications leveraging PySpark and PySpark-SQL for effective data extraction, transformation, and
integration into SQL databases.
 Engineered data pipelines in PySpark, integrating Azure Data Factory and PySpark SQL in Azure Databricks for proficient data handling from
various file formats.
 Crafted and executed SQLpy queries to produce various reports, aiding in insightful data-driven decision-making.
 Gained proficiency in utilizing PySpark SQL for data manipulation in SQL databases, refining the efficiency of data pipeline operations.
 Engaged in developing Python scripts for data ingestion into Azure platforms (Azure Data Lake, Azure Storage, Azure SQL), optimizing data
processing in Azure Databricks.
 Acquired substantial experience with Brinqa for vulnerability risk management, thereby boosting organizational security and risk assessment.
 Operated with Azure Data Lake and Azure SQL, adept in table creation and query formulation on Azure SQL servers, leading to improved data
management.
 Utilized neo4j in conjunction with PySpark for efficient data extraction from neo4j databases, a critical component of the ETL pipeline.
 Maintained vigilant oversight of Splunk dashboards to monitor pipeline failures and performed log analysis for issue resolution, ensuring pipeline
reliability.
 Expertly developed various reports and dashboards using Tableau Visualizations, significantly enhancing data interpretation and presentation.
 Created comprehensive Tableau bar graphs and scatter plots, delivering detailed summary reports and dashboards for improved data insights.
 Implemented Looper and Concord for continuous integration and deployment, optimizing development workflows.
 Demonstrated mastery in Linux commands and effectively scheduled data processing workflows using crontab for automated operations

Skillfully developed and maintained an ETL framework using PySpark, which included daily runs, error handling, and logging, thereby enhancing data processing efficiency.
Pioneered the development of PySpark applications leveraging PySpark and PySpark-SQL for effective data extraction, transformation, and integration into SQL databases.
Engineered data pipelines in PySpark, integrating Azure Data Factory and PySpark SQL in Azure Databricks for proficient data handling from various file formats.
Crafted and executed SQLpy queries to produce various reports, aiding in insightful data-driven decision-making.
Gained proficiency in utilizing PySpark SQL for data manipulation in SQL databases, refining the efficiency of data pipeline operations.
Engaged in developing Python scripts for data ingestion into Azure platforms (Azure Data Lake, Azure Storage, Azure SQL), optimizing data processing in Azure Databricks.
Acquired substantial experience with Brinqa for vulnerability risk management, thereby boosting organizational security and risk assessment.
Operated with Azure Data Lake and Azure SQL, adept in table creation and query formulation on Azure SQL servers, leading to improved data management.
Utilized neo4j in conjunction with PySpark for efficient data extraction from neo4j databases, a critical component of the ETL pipeline.
Maintained vigilant oversight of Splunk dashboards to monitor pipeline failures and performed log analysis for issue resolution, ensuring pipeline reliability.
Expertly developed various reports and dashboards using Tableau Visualizations, significantly enhancing data interpretation and presentation.
Created comprehensive Tableau bar graphs and scatter plots, delivering detailed summary reports and dashboards for improved data insights.
Implemented Looper and Concord for continuous integration and deployment, optimizing development workflows.
Demonstrated mastery in Linux commands and effectively scheduled data processing workflows using crontab for automated operations.

Spearheaded the development of ETL pipelines into and out of the data warehouse, enhancing reporting accuracy and data accessibility with advanced SQL reports.
Orchestrated the creation and management of S3 buckets, reinforcing data security and access control through stringent IAM roles policies.
Authored PySpark code for AWS Glue jobs and EMR, streamlining data processing and integration within AWS services.
Designed and executed an efficient ETL process in AWS Glue using PySpark, enabling effective data migration from various sources like S3 and RDBMS into AWS Redshift, complemented by Athena for streamlined reporting.
Demonstrated expertise in AWS Redshift by engineering ETL jobs that improved data extraction and loading processes.
Played a key role in constructing ETL pipelines using AWS Data Pipelines, facilitating seamless data transfer and processing.
Implemented Apache Airflow for superior orchestration of data pipelines, enhancing scheduling, monitoring, and workflow authoring.
Established a comprehensive monitoring framework using CloudWatch for Lambda functions, Glue Jobs, and EC2 hosts, ensuring optimal system performance and reliability.
Designed and implemented 30+ data pipelines to transform live data into Azure Data Factory pipelines, performed ETL operations using Snowflake.
Developed serverless orchestration for data flow between S3, Redshift, and RDS using Lambda and Step Functions, streamlining processes.
Employed Step Functions for seamless integration and orchestration of Glue jobs, Lambda functions, data pipelines, and data warehouse.
Managed MongoDB databases on the cloud, designing efficient database structures and executing MongoDB queries for optimal database operations.

Expert in applying Agile methodologies in data analysis projects, achieving a 30% quicker adaptation to changing requirements and a 20% boost in project completion rate, ensuring timely and flexible analytical solutions.
Utilized Power BI to develop interactive dashboards and reports, resulting in a 25% increase in stakeholder engagement and a 40% faster decision-making process by improving business intelligence and data visualization.
Proficient in using the R language for statistical analysis and graphics, enhancing data analysis efficiency by 40% with advanced packages and scripts, leading to more precise and insightful data-driven strategies.
Skilled in crafting interactive and detailed visualizations using Matplotlib and Seaborn, specializing in custom data plots and charts for clear and informative presentations.
Focused on enterprise data visualization, adept in using Tableau Desktop and Server to convert complex data sets into engaging visual stories, improving comprehension of key performance metrics.
Effectively supported all production analytics, demonstrating a strong capability in resolving a variety of data and analytics issues, which contributed to a 40% decrease in system downtime and a 35% improvement in overall system reliability, ensuring uninterrupted analytical operations and insight generation.
Proficient in managing MySQL schema objects including Tables, Views, and Indexes, and maintaining referential integrity.
Expertly converted user requirements into technical solutions, achieving a 30% improvement in database performance and a 25% increase in user satisfaction through tailored and efficient data structures.