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About me (Registered since 09/09/2025)
Data Engineer with 5+ years experience in Machine Learning pipeline development, data engineering, and
analytics. Proven expertise in end-to-end Machine Learning solutions, Machine Learning Ops implementation,
and large-scale data platforms. Strong background in Python, cloud computing, and data architecture with
demonstrated business impact. Currently pursuing Master’s in AI Systems at NUS.
Education
- August 2025 - August
- August 2015 - August 2019
Work Experience
-
March 2023 - July 2025
Symphony AI, India
Data Engineer
Engineered backend infrastructure on Snowflake, reducing client deployment time by 70%.
• Orchestrated ML pipelines for automated model deployment across retail clients, improving onboarding
efficiency by 75%.
• Built an internal LLM-based chatbot for API documentation and knowledge management.
• Authored reusable Python libraries for Snowflake integration, standardizing development processes.
• Structured scalable data architecture to support real-time analytics and weekly refresh cycles.
• Refined batch queries, cutting runtime by 50% and lowering refresh cycle costs by 60%.
• Deployed a cost-efficient Azure batch scheduling system, reducing operational expenses by 50%.
• Migrated the entire API framework from Yellowbrick to Snowflake, incorporating query optimizations to
enhance performance and efficiency by 30%. -
April 2020 - March 2023
Symphony AI, India
Associate Software Engineer
• Developed ML applications on Snowflake platform with performance optimization using Vaex and Dask
• Established company-wide Machine Learning Ops standards and best practices
• Built high-performance REST APIs handling large-scale dataset processing
• Optimized SQL performance through query profiling, improving response times by 50%.
• Implemented multithreading Unix architecture for enhanced application performance
• Led backend setup for CINDE application with complete ETL transformation pipeline
• Automated Azure pipeline creation using PowerShell, reducing setup time by 60%.
• Developed ETL processes for client data migration to cloud platforms (Netezza, Yellow Brick)
• Collaborated with Data Science team on ML model integration and production deployment
• Containerized Python applications with Docker, enabling scalable deployment on Microsoft Azure. -
July 2019 - April 2020
Symphony AI, India
Intern
• Developed optimized SQL objects (tables, views, procedures, and queries) in collaboration with business
analysts to support reporting and analytics requirements.
• Automated recurring backend operations using Unix Shell scripting, improving process efficiency and
reducing manual effort.