Jun 2023 – Sep 2025 · 2 yrs 3 mos · Hyderabad, Telangana, India · Hybrid

• Spearheaded the development of customer-focused features using Python, Flask, FastAPI, REST APIs, and PostgreSQL, enhancing user experience, performance, and overall application reliability.
• Built seamless Outlook integration using the Microsoft Graph API, streamlining accessibility and reducing manual workflows across the platform.
• Engineered integration pipelines with major platforms via webhooks, enabling real-time upstream and downstream file ingestion and improving interoperability.
• Developed and optimized backend APIs and frontend interfaces, fixed key production issues, and launched an interactive dashboard with automated email scheduling for report delivery.
• Designed and implemented a robust Role-Based Access Control (RBAC) system using Python/Flask, supporting multi-tenant environments with dynamic, database-driven permission mapping to strengthen data security.
• Collaborated with cross-functional teams to perform penetration testing, mitigate vulnerabilities, and enhance product security, integrity, and compliance.
• Achieved 95% test coverage, ensuring software reliability and reducing regression risks during deployments.
• Migrated Airflow from Docker to Kubernetes, replacing shell scripts with Python operators, enabling parallelism and resource optimization that reduced DAG execution time from 16 hours to 4 hours and cut system downtime by 80%.
• Addressed memory leaks and performance bottlenecks, improving overall system stability, scalability, and responsiveness.
• Implemented API-level caching for frequently accessed endpoints, reducing latency and improving response times for critical services.
• Transformed static mapping tables into fully configurable, customer-specific models, enabling scalable and flexible API integrations.
• Developed a centralized email service with configurable templates and unified tracking, standardizing outgoing communication and improving operational efficiency.

Aug 2022 – Jun 2023 · 10 mos · Hyderabad

• Spearheaded the design and development of a scalable automated Word document generation system using Python, Flask, Python-docx, Matplotlib, and Postgres, reducing manual documentation efforts by 90% and significantly improving operational efficiency for thousands of electrical transformers.
• Translated complex client requirements into dynamic, customizable automated workflows, ensuring strict adherence to formatting, compliance, and data integrity standards, resulting in faster and more accurate document delivery.
• Led cross-functional teams to integrate Python modules into the TDMS project, achieving a 25% increase in project delivery efficiency and streamlining collaboration between software, QA, and operations teams.
• Implemented dynamic templates with real-time data visualizations, enabling users to generate client-ready reports flexibly and reducing issue resolution time by 70%.
• Developed robust error-handling mechanisms, logging frameworks, and performance optimizations, enhancing system reliability, reducing downtime, and enabling rapid iteration for new document formats.
• Ensured high-quality code through unit and integration testing with Pytest, achieving 85% code coverage, thereby supporting maintainability, seamless deployment, and operational stability.
• Optimized backend workflows and automated repetitive tasks, allowing the team to focus on higher-value activities and significantly boosting overall productivity.
• Demonstrated the impact of combining automation, software engineering best practices, and data visualization to solve complex operational challenges and establish scalable solutions for future projects.

Feb 2022 – May 2022 · 3 mos

Jan 2022 – Jul 2022 · 6 mos

• As part of my internship, I implemented a Slowly Changing Dimension (SCD) Type 1 pipeline to handle updated data efficiently, where new data overwrites existing records. This project gave me hands-on experience with ETL processes, Hive, Sqoop, HDFS, and MySQL.
• Process Flow:
• 1. Automated scripts to transfer files from the local file system to MySQL, ensuring seamless data ingestion.
• 2. Created a Sqoop job to load data from MySQL into HDFS (Hadoop Distributed File System), facilitating distributed storage and processing.
• 3. Designed and populated internal Hive tables by transferring data from HDFS.
• 4. Created external Hive tables with dynamic partitioning and loaded data from internal tables to enable optimized querying.
• 5. Applied SCD Type 1 logic to update records, ensuring that only the latest data was retained.
• 6. Exported the updated data from Hive external tables back to SQL for data reconciliation and validation, completing the end-to-end pipeline.
• This project enhanced my understanding of ETL workflows, data warehousing concepts, and Hadoop ecosystem tools, and gave me practical experience in building automated, scalable data pipelines.

Jul 2021 – Aug 2021 · 1 mo · Bangalore Urban, Karnataka, India