● Mentored students in Data Structures, Large-Scale Data Structures, and Python programming, providing tutoring and grading support for approximately 150 students per course, fostering a deep understanding of data engineering principles. ● Personalized tutoring sessions to enhance student comprehension and performance in complex topics, such as algorithm analysis, data structure optimization, and data processing techniques. ● Streamlined grading and feedback processes for assignments and exams in Data Structures, Large-Scale Data Structures, and Python courses, reducing turnaround time by 30% and ensuring timely, constructive feedback, analogous to optimizing data workflows in ETL processes. ● Adapted data engineering skills to maintain accurate grade records, employing efficient data management techniques to ensure data integrity and accessibility. ● Facilitated effective communication between students and faculty, leveraging data visualization and reporting skills to provide clear and actionable insights into student performance and progress. ● Applied data analysis and quality management principles to develop robust assessment methods, ensuring fair and consistent evaluation of student work. ● Automated solutions for repetitive administrative tasks, akin to automating data pipelines, improving efficiency and accuracy in grade record maintenance. ● Guided students in practical applications LSDS and algorithms, preparing them for real-world data engineering challenges and enhancing skills mutually. ● Workshops on advanced Python programming and data processing techniques, equipping students with essential skills for data engineering roles. ● Collaborated with faculty to design and update curriculum content, integrating the latest data engineering concepts and practices to keep coursework relevant and challenging.

● Facilitated stakeholder sessions to assess existing on-premises SAP infrastructure, data sources, and compliance requirements, ensuring alignment with AWS capabilities for a seamless migration process. ● Architected and deployed secure, scalable AWS solutions using Amazon S3 for data storage, Amazon Redshift for data warehousing, and Amazon QuickSight for data visualization, enhancing data migration efficiency and accessibility for stakeholders. ● Configured and managed AWS resources, including EC2 instances, VPCs, and IAM roles, to establish secure and isolated environments critical for data migration and processing tasks, ensuring data integrity and compliance. ● Led the ETL process for SAP data migration from on-premises to AWS, utilizing AWS Glue and PySpark on AWS EMR for data extraction, transformation, and loading (ETL), ensuring high data quality and consistency throughout the migration. ● AWS Data Migration Service (DMS) to extract data from on-premises SAP systems, facilitating seamless and efficient data transfer to AWS cloud storage solutions like Amazon S3 and Amazon Redshift, optimizing storage and retrieval processes. ● Designed and executed ETL pipelines for SAP data, using AWS Glue and PySpark for data transformation and cleansing, ensuring reliable data integration and maintaining high data quality across multiple AWS services. ● Performed comprehensive data validation and optimization post-migration, ensuring the accuracy, integrity, and completeness of SAP data in Amazon Redshift, while optimizing query performance for efficient data access and analysis. ● Developed interactive dashboards and reports using Amazon QuickSight and Power BI, enabling stakeholders to gain actionable business insights from SAP data through real-time data visualization, improving decision-making processes. ● Implemented IAM roles, AWS KMS, and compliance measures such as encryption and auditing with AWS CloudTrail, ensuring robust data security and adherence to regulatory standards, including HIPAA, during SAP data migration. ● Utilized AWS CloudWatch for monitoring and logging AWS resources and applications, ensuring continuous performance optimization, real-time issue identification, and quick resolution of operational disruptions during and after SAP data migration. ● Leveraged advanced Excel functions, including VLOOKUP, XLOOKUP, PivotTables, and Power Query, to automate complex data analysis, improving accuracy, reducing manual workload, and enabling real-time reporting for key stakeholders in relation to SAP data. ● Conducted training and mentoring sessions for team members and stakeholders on AWS infrastructure, SAP data integration, and best practices, ensuring smooth adoption, effective usage, and knowledge transfer for ongoing operations. Projects: Data Warehousing. Disease Prediction Model Using Machine Learning. Deep State Testing. Covid Support System – Django Web Application.