Data Engineering professional experienced in building scalable data pipelines and cloud-based data platforms on AWS. Skilled in developing Python-based ETL workflows, automating data processing pipelines, and enabling reliable data integration for analytics and reporting systems.
Hands-on experience with AWS services including Lambda, S3, DynamoDB, RDS (PostgreSQL/MySQL), Batch, EventBridge, SQS, and Step Functions to build event-driven and serverless data architectures. Experienced in Amazon Redshift, Redshift Spectrum, and Materialized Views for cloud data warehousing and high-performance analytical queries.
Strong background in SQL performance optimization, reducing query execution time from 10 minutes to under 10 seconds through query plan analysis and indexing strategies. Experienced in real-time data replication using Qlik, CI/CD workflows with GitHub, and working in Agile environments to deliver reliable data solutions.
Core Skills: Python • SQL • AWS • ETL • Data Pipelines • Amazon Redshift • PostgreSQL • Lambda • S3 • Step Functions • EventBridge • DynamoDB • Query Optimization • CI/CD
