Kavya Bijja

• Implement sharded update jobs on AWS Glue and EC2 to support long-running incremental data refreshes, reducing processing time and ensuring scalable, fault-tolerant updates. • Built automated web scraping systems using Browserless to handle CAPTCHA-protected workflows, enabling stable and high-volume data ingestion with minimal manual intervention. • Developed Python-based dataset enrichment tools and schema migration scripts to resolve structural inconsistencies, improving data integrity and reducing downstream AI errors. • Designed and tested multi-phase AI evaluation workflows, including citation ordering, response validation, and ranking logic, improving tutoring and legal search accuracy while reducing hallucination risks.

• Designed and delivered hands-on labs in Python, SQL, and distributed systems (Spark, MapReduce) for 60+ graduate students, reinforcing data engineering concepts through real-world ETL case studies. • Guided student projects on data modeling and warehousing, improving overall project success rate by 30%. • Conducted workshops on AI/ML integration with big data platforms, enabling students to analyze large-scale datasets and generate actionable insights.

• Supported and optimized backend systems for cloud-based applications by diagnosing and resolving incidents using Splunk and Wireshark, resolving 95% of issues within SLA and boosting platform reliability by 18%. • Automated diagnostic scripts and escalation workflows using scripting tools, streamlining troubleshooting processes and improving mean time to resolution by 22%. • Delivered responsive on-site and remote IT support by collaborating across teams and applying strong analytical and problem-solving skills, ensuring a positive user experience and reducing service disruptions. • Managed departmental data and system access using Excel, Tableau, and SharePoint, ensuring compliance with policies while enhancing coordination and operational transparency across teams.

• Led development of a Generative AI-powered e-commerce analytics platform using Quicksight with Amazon Q, and Content enhacement via Bedrock, reducing analysis time by 50% and boosting customer engagement by 22%. • Improved integration patterns for 3 major AWS services (Lambda, S3, CloudFormation) by analyzing 100+ customers feedback and aligning solutions with evolving enterprise architecture standards, reducing integration issues by 20%. • Cut deployment time by 40% by designing and delivering 10+ reusable infrastructure templates with AWS CloudFormation and CDK, enabling faster release cycles and lowering manual configuration errors by 30%

• Responsible for the automation of data migration tools and accelerators. • Built full-stack web development tools with Python and React which help the cross-platform data migration from various source databases like Teradata, Oracle, Postgres, Snowflake, etc., to target the of Bigquery and Databricks. • Worked on migration Successfully migrating the Monolithic architecture to a Microservices architecture, enhancing system scalability and fault tolerance. • Performed comprehensive unit testing on web applications, skillfully optimizing and meticulously eliminating any potential vulnerabilities. • Collaborated with the DevOps team to deploy in cloud virtual machines and Web apps. • Built a lineage tool to extract object dependencies in databases and developed clustering and object sequencing solutions for the objects in the database using the graph data structure and orient DB database. • Developed a parser to extract dependencies on database objects in SSIS and Informatica. • Created interactive dashboards in Power BI to bring insights about the usage and maintenance of cloud products in the Google Cloud Platform. • Validated migrated data across databases in parallel using Spark SQL and AI-based tools. • Developed generative AI-based solutions using Vertex AI and Open AI for optimizing and documenting the generated queries.

• Extensively trained in utilizing software development and Data Engineering concepts and principles, enabling me to collaborate seamlessly with teams to efficiently address real-life client challenges. • Had hands-on experience in implementing the complete development cycle, encompassing development to deployment, while working closely with highly skilled professionals.

• Engaged in collaborative efforts with fellow students to deepen our understanding of computer science concepts. • Demonstrated practical expertise by constructing a range of machine learning models and successfully developing products such as a web scraper, music crawler, and a robust face recognition system.

IFT 510 - Principles of Computer and Information Technology Architecture. IFT 540 - Information Systems Development. IFT 520 -Advanced Information Systems Security IFT 511 -Analyzing Big data IFT 530 -Advanced Database Management Systems IFT 533 -Data visualization and Reporting for IT IFT 560 -Cloud Architecture for IT

Actively engaged in collaborative workshops focused on Flutter mobile app development, fostering valuable partnerships with numerous fellow students. Publications: A. Hafsana, Athul Vijay, Manas P. Vinayan, Bijja Kavya and T. Jagadeesha. (2022). "Comparative Study of Magnetorheological Brakes from Magnetic Theory Perspective by Finite Element Methods". Smart Innovation, Systems and Technologies, vol 292 (pp 339-348).