Data Analyst
Current● Involved in the entire Software Development Life Cycle – Analysis, Design, and Development – and coordinated with the team using Agile Methodologies.● Implemented PySpark for data processing to handle data from various RDBMS and streaming sources; used Redshift for the Data Warehouse service.● Built an end-to-end data pipeline and performed analytics using the AWS stack (EMR, EC2, S3, RDS, Lambda, Glue, SQS, Redshift).● Implemented end-to-end data quality checks and monitoring… Show more ● Involved in the entire Software Development Life Cycle – Analysis, Design, and Development – and coordinated with the team using Agile Methodologies.● Implemented PySpark for data processing to handle data from various RDBMS and streaming sources; used Redshift for the Data Warehouse service.● Built an end-to-end data pipeline and performed analytics using the AWS stack (EMR, EC2, S3, RDS, Lambda, Glue, SQS, Redshift).● Implemented end-to-end data quality checks and monitoring alarms for ETL pipelines, minimizing data delay friction.● Solely maintained Amazon Redshift cluster and AWS architecture, automating data pipelines and supporting data lakes.● Developed data pipelines to extract data from various sources, transformed it as per the business requirements, and loaded it into Redshift for analysis.● Employed AWS Kinesis to capture real-time data from various sources, handling terabytes of data.● Worked on CI/CD solution, using Git and Jenkins to set up and configure the big data architecture on AWS cloud platform.● Responsible for writing Unit Tests and deploying production level code with the assistance of Git version control. Show less