Nischitha Mandala

• Automated QA workflows and CI/CD pipelines using GitHub Actions and Python scripts.
• Designed Python scripts for data parsing and transformation with Pandas and NumPy.
• Developed microservices deployed via Flask and FastAPI, integrated with MS SQL Server and Oracle.
• Implemented binary and linear search functions for efficient data processing modules.
• Established unit and integration tests for RESTful APIs using Pytest and Unittest frameworks.
• Utilized Kubernetes and Docker for container orchestration to streamline deployment processes.
• Managed GitHub repositories for effective release management and continuous integration.

Environment: Python, Pandas, NumPy, GitHub Actions, Docker, Kubernetes, REST API, MS SQL Server, Oracle, Flask, FastAPI

• Developed Python scripts for GitHub automation, including auto-merging PRs and release tagging.
• Designed data ingestion and ETL pipelines with Python and Pandas for efficient backend reporting.
• Automated testing and deployment of RESTful APIs within CI/CD pipelines.
• Created search functionalities using custom algorithms, such as binary and linear search.
• Produced comprehensive QA scripts for backend services, generating detailed code coverage reports.
• Implemented string parsing utilities in Python for data cleanup from various sources.

Environment: Python, Pytest, Pandas, GitHub, Azure DevOps, REST API, Jenkins, SQL Server.

• Wrote Python scripts for GitHub automation, including auto-merging PRs and tagging releases.
• Designed data ingestion and ETL pipelines with Python and Pandas to optimize backend reporting.
• Automated testing and deployment of RESTful APIs within CI/CD pipelines.
• Created custom search functionalities using algorithms such as binary and linear search.
• Developed QA scripts for backend services, producing detailed code coverage reports.
• Implemented string parsing utilities in Python for efficient data cleanup from various sources.

Environment: Python, Pytest, Pandas, GitHub, Azure DevOps, REST API, Jenkins, SQL Server

• Automated software testing lifecycle using Python scripts and Pytest within GitHub CI pipelines.
• Created data processing scripts with Pandas for handling client-specific datasets.
• Built modular scripts to automate reporting, QA validations, and test case executions.
• Developed string processing utilities for API testing and log analysis.
• Maintained and optimized binary search tree logic and linear search modules for internal systems.

Environment: Python, GitHub Actions, Pandas, NumPy, Pytest, Flask, Oracle SQL, Azure DevOps.