Vinodh Kumaar Cherukupalli
Development
MA, United States
Skills
Data Engineering
About
VINODH KUMAAR CHERUKUPALLI's skills align with System Developers and Analysts (Information and Communication Technology). VINODH also has skills associated with Database Specialists (Information and Communication Technology). VINODH KUMAAR CHERUKUPALLI appears to be a low-to-mid level candidate, with 4 years of experience.
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Work Experience
Apprenticeship | SOFTWARE VULNERABILITIY ANALYSIS
ML4CYBER
September 2023 - December 2023
- Conducted comprehensive data analysis, implementing data pre-processing techniques including One-Hot Encoding, handled the near Zero Variance, feature engineering Implemented XG boost, and Naive Bayes techniques to compare the performance of the models based on the ROC, AUC, and Accuracy values. Improved the functionality of application by fixing the JSON file parsing issue there by ensuring data consistency
Data Engineer
TELEPERFORMANCE
April 2023 - September 2023
- Designed and implemented scalable data pipelines for ingesting, processing, and transforming large volumes of data from sources (Service Now, Dynamic 365, Workday etc.) to the Azure Delta Lake Structured data within Azure Data Lake Storage Gen2 for hierarchical namespace and optimized for integration with Synapse Analytics Transitioned enterprise data from on-premises storage to Azure Delta Tables ensuring seamless data transition Extracted the data of different file formats (CSV, Excel, Parquet etc.) from Azure blob storage and converted them into Delta tables using Spark SQL notebooks Developed and managed golden tables in Azure Synapse Analytics to serve as the single source of truth for key business entities across multiple departments Proactively worked on query optimizations and code automations to build a PySpark notebook for tables creation Collaborated with business analysts and data scientists, providing them with reliable datasets for advanced analytics and reporting in Power BI
Apprenticeship
EQUIPMENT AND COST OPTIMIZATION
January 2023 - April 2023
- Built a prediction model to provide insights for the potential future growth in effective equipment utilization and cost reductions Designed and implemented a Power BI dashboard to visualize and interpret the company's financial data Performed data quality assessments identified and resolved data issues, resulting in 98% data accuracy and executed ad hoc SQL queries to gain insights into equipment usage trends
Software Engineer
TATA CONSULTANCY SERVICES
June 2019 - November 2021
- Orchestrated the strategic planning and execution of migrating three critical AIG Insurance applications to Oracle Exadata, including cloud adaptation initiatives, to optimize technological infrastructure and operational agility. Conducted comprehensive data analysis by designing and implementing stored procedures, queries, views, and functions, empowering data-driven decision-making, and strategic insights. Mastered the adoption of automation for SQL scripts deployment, utilizing Jenkins for enhancing continuous integration and deployment (CI/CD) processes, significantly improving operational efficiency. Designed and implemented an innovative solution for automating policy premium calculations, utilizing JAVA and SQL stored procedures, leading to a significant reduction in manual processing time by 40% and increasing operational efficiency. Enhanced stakeholder engagement and operational support by proactively resolving Level 2 and Level 3 issues, adhering to SLAs, and employing preemptive monitoring strategies to minimize system downtime by 30%. Led data integrity initiatives by identifying, analyzing, and resolving discrepancies in data loads with custom SQL scripts, ensuring accuracy and reliability of business-critical data. Managed the end-to-end migration and transformation of the internal ticketing trends dashboard from QlikView to Power BI, facilitating advanced data visualization techniques and improved analytical reporting for business users.
Apprenticeship
PATH CREATORS
January 2019 - June 2019
- Used an industrial mobile network dataset from a cloud server to perform simulations and analyze the patterns to identify spammers. Identified the characteristics of spammers and normal users in an industrial mobile network. Implemented ML model using JAVA and designed a MYSQL database to store and record the data at every point. Developed multiple segments such as User, Admin and provided segment level security features to handle the access restrictions for spammers. Designed classification based on machine learning algorithm for mapping data samples into two classes. Automated data modelling task which increases the precision of the model by expanding the training set.
Education
Northeastern University
Master of Professional studies in Analytics
January 2022 - December 2023
