Rakesh A Email & Phone Number

Plainfield, Nj, Us

• Worked on a project which helps automate the process of synchronizing all the files from storage to AWS S3 bucket on a nightly basis using AWS lambda functions, DynamoDB, S3 Bucket, SQS, Secrets Manager, IAM, Cloud Watch.• Used Python for data extraction, transformation, and aggregation from multiple source systems for business use cases• Designed and setup Enterprise Data Lake to provide support for various uses cases including Analytics, pro-cessing, storing, and Reporting of voluminous, rapidly changing data.• Developed API for using AWS Lambda to manage the servers and run the code in the AWS.• Utilized S3 buckets for file storage and backup on AWS cloud.

Los Angeles, California, United States

• Worked in all the phases of SDLC and agile development methodologies including SCRUM, involved in daily SCRUM meetings to keep track of the ongoing project status and issues using JIRA.• Implemented AWS solutions using E2C, S3, RDS, EBS, Elastic Load Balancer, Glue Pipelines, Glue Crawler, Auto scaling groups, Optimized volumes, and EC2 instances and created monitors, alarms, and notifications for EC2 hosts using Cloud Watch.• Used Spark SQL to process the huge amount of structured data• Worked on Data Analysis, processed Data and performed Analytics on the data from various systems. • Performed transformations and actions on the datasets using Spark Core for log transaction aggregation and analytics• Worked on Spark Data Frames and Spark SQL for Various Data Analytics Processing• Imported the data from different sources like AWS S3 into Spark Data Frame• Imported data from AWS S3 and into Spark Data Frames and performed transformation and actions.• Designed and deployed Hadoop cluster and different Big Data analytic tools including Pig, Hive, HBase, Oozie, Sqoop, Kafka, Spark, Impala.

Hyderabad, Telangana, India

• Migrated data (Amazon Connect Call Metrics) from legacy systems (Cassandra) to cloud based (AWS) Snow-flake Datawarehouse• Developed spark scripts by using PySpark shell command as per the requirement from Business• Implemented Spark using Python utilizing data frames and spark SQL API for faster processing of data• Used NumPy, pandas, SQLalchemy and sci-kit packages to support the migration in Python• Leveraged distributed computing and server less architecture such as AWS EMR & AWS Lambda, to develop pipelines for transforming data.• Created AWS Data Pipelines from S3 to Red shift DB. • Migrated on premise database structure to Redshift data warehouse• Wrote SQL queries to perform data quality checks/validation in AWS snowflake as compared to legacy data• Created Mappings, Workflows, Worklets and Scheduling Jobs for Data Processing as per the business requirements• Installed and Snowflake configured Hadoop and responsible for maintaining cluster and managing and re-viewing Hadoop log files.

Hyderabad, Telangana, India

• Exported the analysed data to the relational databases using Sqoop for visualization and to generate reports for the BI team.• Worked with AWS batch processing of data sources using Apache Spark.

Hyderabad, Telangana, India

• Performed end- to-end Architecture & implementation assessment of various AWS services like Amazon EMR, Redshift, S3.• Created Pyspark frame to bring data from DB2 to Amazon S3• Coordinated with multiple teams to gather requirements, propose design solutions, create implementation and validation plans for process deployment.