Keerthi Chintala

Master's

Computer Science

Analyst

- Technologies: Abinitio, Python, SQL, Linux, Bash Scripting - Responsibilities - Involved in Analysis, Design, Process interfaces design and documentation - Developed various data loading strategies and performed various transformations for analysing datasets - Developed and maintained complex Ab Initio graphs for extracting, transforming, and loading data from various source systems into data warehouses - Designed and implemented data integration solutions to support business intelligence and reporting requirements, ensuring data quality, accuracy, and consistency - Conducted data analysis and profiling to identify patterns, trends, and anomalies in large datasets, providing actionable insights to stakeholders - Collaborated with business analysts, data architects, and stakeholders to gather requirements, define data integration strategies, and deliver solutions that meet business objectives - Worked on performance tuning and optimization of Ab Initio graphs to improve processing speed, resource utilization, and scalability - PROJECT - 2 - December 2022 - Project Name: Secure Cloud Data Storage Infrastructure - Technologies: AWS S3, VPC, AWS IAM - Designed and implemented a secure data lake using S3 buckets within a private VPC environment - Configured VPC subnets and security groups to restrict access to data stored in S3 - Created and assigned IAM roles and policies to control user and application access to specific data resources within the S3 buckets - PROJECT - 3 - June 2023 - Project Name: Big Data ETL Pipeline with Glue and S3 - Technologies: AWS Glue, S3, EC2, Apache Spark - Selected a public movie review dataset stored in S3 - Launched and configured an EC2 instance with Apache Spark for large-scale data analysis - Utilized AWS Glue to extract and potentially pre-process the movie review data from S3 for efficient analysis on the EC2 instance - Performed data exploration, sentiment analysis, or built a basic machine learning model to analyze the reviews using Spark or Python libraries on the EC2 instance - PROJECT - 4 - Project Name: Interactive Stock Market Trends - Technologies: AWS E2, S3, Flask, PowerBi - Developed a web application using Flask (or Django) to retrieve stock market data from S3 - Configured an EC2 instance to host the web application - Implemented functionalities to access and retrieve stock data from S3 buckets using the AWS SDK or other tools - Integrated data visualization tool PowerBi to display the retrieved stock data in an interactive format within the web application