Nikhil Kumar Pasupuleti

Project - Led and executed a comprehensive data migration project, seamlessly transitioning critical Healthcare data assets from on-premise source systems (Teradata and Hadoop) to Snowflake. Utilized AWS S3 as a as a secure and efficient bridge for data transfer, adhering to stringent healthcare data privacy and HIPPA security regulations.

Responsibilities -

• Developed and executed complex SQL queries for data extraction, transformation, and loading (ETL) from Teradata and Hadoop to Snowflake.
• Used AWS Lambda to trigger data extraction from Teradata and Hadoop sources. Scheduled Lambda functions to run at specific intervals and also in response to events such as a JSON file being dropped.
• Designed and scheduled AWS Glue ETL jobs, orchestrating the execution of multiple transformations and loading tasks in parallel, expediting the migration process.
• Using MySQL to monitor Lambda Functions for tracking job execution, identifying issues, and gaining insights.
• Integrated AWS Glue jobs with AWS Lambda functions to automate data extraction, ensuring timely and accurate loading of healthcare data from on-premise sources to AWS S3.
• Integrated AWS Lambda functions into our Step Functions workflow so that each step in the workflow can invoke a Lambda function to perform specific tasks, such as data extraction, transformation, loading, and validation.
• Used AWS EMR clusters to execute data cleansing and enrichment tasks, improving data quality and alignment with the Snowflake schema.
• Performed real-time analytics on the migrated data, using AWS EMR with streaming frameworks like Apache Kafka and process streaming data before loading it into Snowflake.
• Collaborated regularly with the Off-shore production support to make sure all the jobs were running without any issues.
• Collaborated closely with the IT and compliance teams to navigate stringent regulatory requirements, ensuring HIPAA data standards were met throughout the migration process.

Project: Data migration from Amazon Redshift to S3 bucket for better data management by separating compute and storage, auto-scaling compute clusters and achieving near real-time ingestion without latency in data availability.

Responsibilities -

• Developed approximately 200 ETL jobs in python to extract and load On-prem and Redshift data into AWS S3
• Wrote Python scripts to parse JSON documents and load data into Redshift spectrum tables.
• Used SQL to update and retrieve data. Participated in architecture, design and implementation of back-end features using C++, C#.
• Utilized Kubernetes and Docker for runtime environment of the CI/CD system to build, test and deploy.
• Prepared the complete data mapping for all the migrated jobs using SSIS.
• Deploy and monitor ML models in production.
• Involved in Development, Consumption and Deployment of services using C#.Net.
• Worked on front-end software development for UNIX. Analyzed code defects and failures and presented code refactors and design fixes.
• Contributed to daily scrum meetings with team updates.

• Imaging specialist with a role to intake all student documents submitted to the university
• Verify and approve transcripts by ingesting into Oracle's Peoplesoft system