Vamsi Krishna Copesetty

• Engineered 14 production ETL/ELT pipelines in 6 months using Azure Data Factory, Databricks, Python, and Linux-based environments, maintaining a delivery pace of one new integration every 2 weeks. Automated ingestion of high-volume financial transaction datasets and implemented monitoring, validation, and recovery controls, reducing manual effort by 85% while achieving 100% scheduled execution reliability. Troubleshot complex operating system, network connectivity, API authentication, and data integration issues across distributed cloud environments, reducing production incident resolution time by approximately 70%. Developed Python-based automation and REST API integrations with external ERP platforms to synchronize transaction status updates and enterprise master data, reducing downstream data discrepancies by 35%. Collaborated directly with management stakeholders, business users, and technical teams to gather requirements, present technical solutions, and deliver scalable data integration workflows. Designed reusable parameterized frameworks for multi-region deployments, reducing onboarding time for new data sources by 60% while improving maintainability and operational consistency. Implemented schema validation, idempotency controls, logging, and proactive monitoring to ensure secure, recoverable, and production-safe workflows supporting global business operations.

Supported distributed telemetry and data collection workflows for XR prototype hardware used in Google Research labs Diagnosed and resolved OS-level, connectivity, and data-transfer failures on Linux devices, restoring functionality and reducing team downtime Executed command-line operations to transfer and validate large-scale datasets across connected devices Performed hardware validation, firmware checks, and peripheral testing on experimental prototype hardware Authored troubleshooting documentation and SOPs adopted across the support team Escalated critical hardware-software integration issues to engineering, improving cross-team resolution speed

Onboarded diverse data sources into Splunk, cutting time-to-value for new integrations Streamlined implementation strategies, reducing project delivery timelines by 20% Built cost-effective high-availability Splunk solutions, reducing infrastructure costs by ~25%

Managed data ingestion pipelines and built dashboards for Splunk integrations Coordinated workflows via JIRA, improving data ingestion efficiency by 35% Maintained 95% system uptime through proactive monitoring and issue resolution

Designed and maintained AWS lab environments (EC2, Load Balancer, CloudFront) supporting large-scale distributed application exercises Provisioned and configured cloud resources, resolving IAM, networking, and deployment issues across student environments Diagnosed Linux boot failures, permission errors, and misconfigured services using CLI tools and system logs Built and maintained virtualized Windows and Linux environments supporting hundreds of concurrent student users

Coursework: Emerging IS Technology, Information Systems Security, Information Systems Infrastructure, Strategic Decisions, Management Information Systems and Design, Ethics & Social Responsibility

Achieved a gold medal distinction for my excellent academic record in December 2022 Coursework: Advanced Database Management Systems, System Administration of UNIX, Information Systems Development, Cloud Architecture, Natural Language Processing, Analyzing Big Data, Advanced Big Data Analytics/AI, Data Visualization and Reporting for Information Technology, Developing Security Policy.

Relevant Coursework: Operating Systems, Software Engineering, Internet Programming, Artificial Intelligence, Database Management Systems