Akhil Pragallapati

Master's

Computer Information Systems

Tata Consultancy Services

Data Engineer

- Automated data extraction, transformation, and loading processes using Python, significantly reducing manual intervention and processing time, and ensuring consistent and accurate data flow across various systems - Employed Scikit-learn and Matplotlib to develop machine learning models and generate comprehensive visualizations, respectively, optimizing datadriven - Streamlined ETL processes using SQL Server Integration Services (SSIS), leading to a reduction in data processing errors and load times, thereby - Developed and maintained over 20 interactive Tableau dashboards to visualize complex datasets, enabling stakeholders to gain real-time insights into - Administered MongoDB database instances, optimizing performance and improving database response times by executing over 200 queries and managing AWS CloudWatch for data workflow monitoring - Improved data quality through collaborative problem-solving with engineering teams, employing SQL and data structures to identify and resolve data - Leveraged Excel's VBA (Visual Basic for Applications) scripting capabilities to automate repetitive data processing tasks, significantly reducing manual - Implemented ETL pipelines using Python and SQL, improving business efficiency from concept to deployment by automating data extraction - Managed multi-terabyte datasets using Hadoop Distributed File System (HDFS), improving data handling efficiency through effective data storage and retrieval strategies. Utilized Spark's Data Frame API to accelerate structured data processing on distributed datasets - Improved system efficiency and reliability through the fine-tuning of data queries using Python and SQL, optimizing data retrieval processes and - Extracted data from Zabbix using Python scripts and set up database schema and workflow using MongoDB, enhancing data organization and accessibility for better system monitoring and performance analysis - Utilized Waterfall methodologies for certain projects to ensure clear project phases and structured progress, enhancing predictability and documentation quality by following a linear and sequential approach to project management - Conducted in-depth data analysis using Python libraries like Pandas, NumPy, to uncover insights and trends that informed program development and resource allocation. Developed interactive dashboards and reports using Power BI to present findings to stakeholders, facilitating informed decisionmaking - Worked closely with social workers, program managers, and other stakeholders to understand their data needs and provide technical support. Used - Developed and deployed automated workflows and data pipelines using tools like Apache Airflow to streamline data processing and reduce manual