VOOTLA PUSHPAK

Associate Data Engineer

Ensono Technologies•  October 2022 - Present•  Chennai

Contributed to the development of a retail data analytics platform on Azure for a UK-based retail company, enhancing sales performance tracking by 20% and improving customer behavior analysis accuracy by 30%. Performed comprehensive quality checks on all incoming data in Azure Data Lake Storage (ADLS) Gen2 to prevent any potential duplication and other critical issues before processing, thereby ensuring the utmost data integrity and reliability. Designed and implemented ETL pipelines in Azure Data Factory with triggers to automate data processing, handling over 1 million records daily in ADLS Gen2, leading to a 30% improvement in data processing efficiency. Leveraged Azure Databricks to process large-scale retail data, applying Spark optimizations to enhance performance and efficiency, resulting in a 25% improvement in sales forecast accuracy and a 15% reduction in inventory costs through advanced data modeling and analysis. Delivered transformed data via Azure Synapse Analytics for Power BI dashboards, boosting analysis effectiveness and increasing stakeholder engagement by 20%. Established a feedback mechanism incorporating input from data analysts to continuously improve data workflow communication, enhancing cross-team collaboration and resolving 95% of workflow issues.

Project Trainee Intern

Wipro•  March 2022 - September 2022

Developed a mini online job portal system, connecting job seekers with employers. Built the web application with JSP, Servlets, MySQL and JDBC, managing 100 user accounts and 50 admin accounts. Managed version control with GitHub, overseeing 20+ code updates and ensuring collaborative development. Configured the application on AWS Elastic Beanstalk, maintaining 99.5% uptime, and integrated CloudWatch for monitoring to improve application stability. Utilized RDS Aurora for database management, supporting up to 500 job listings and applications. Collaborated with co-developers for code reviews and feedback sessions, integrating mentor suggestions to enhance functionality and code quality.