Sep 2024 – Mar 2025 · 6 mos

• Hit pause to step back, learn, and reset

Oct 2023 – Aug 2024 · 10 mos

• Led a 7-member Data Engineering team, delivering 10+ customer enhancements and ensuring timely product releases.
• Designed and implemented scalable ETL pipelines using Apache Airflow and PySpark, orchestrating data workflows across Kubernetes clusters for efficient large-scale data processing.
• Integrated the ELK stack for real-time monitoring and analytics, improving system bottleneck identification and resolution.
• Developed a robust data validation framework with Great Expectations, ensuring data integrity across complex workflows.
• Automated CI/CD pipelines, reducing deployment efforts by 40% and improving operational efficiency.

Aug 2021 – Sep 2023 · 2 yrs 1 mo

• Led a backend team of 3 to implement multi-tenancy support and enhance user management in the Dynamic Demand AI (DDAI) application.
• Re-architected backend systems, migrating from Django-based APIs to FastAPI-based microservices, improving scalability and reducing latency.
• Spearheaded feature enhancements based on customer feedback, leading to improved user satisfaction and retention.
• Developed internal tools like the tenant manager service and config store, significantly improving operational workflows.

Jan 2020 – Jul 2021 · 1 yr 6 mos

• Architected the core backend system for the Dynamic Demand AI application, improving efficiency for demand planners.
• Designed versatile data schema models tailored to customer needs and integrated GraphQL with Django for enhanced API performance.
• Collaborated with demand planning experts to translate business requirements into scalable technical solutions.

Aug 2019 – Dec 2019 · 4 mos · Bengaluru Area, India

• Developed and maintained web applications using AngularJS and Django, improving data processing efficiency by 30%.
• Refactored machine learning codebase, reducing runtime and boosting performance by 30%, resulting in faster and more accurate data analysis.
• Implemented data pipelines with Apache Airflow to streamline data preprocessing from production to analytical servers, ensuring timely data delivery.
• Collaborated with Data Scientists to optimize data flow, reducing preparation time by 20%.

Apr 2019 – Jul 2019 · 3 mos

• Managed two customer applications, overseeing ETL jobs and real-time monitoring, improving system uptime and reducing issue resolution time.
• Developed Flask-based API services for customer-facing applications and internal tools, improving monitoring and configuration management.
• Designed and implemented a scalable AI orchestration platform using Flask microservices, enabling multi-tenant capabilities and improving deployment efficiency.
• Integrated a Celery cluster for asynchronous task execution, enhancing system performance and enabling real-time task management.
• Set up JupyterHub with Active Directory integration for user authentication and version-controlled workspaces.

Jul 2018 – Mar 2019 · 8 mos

• Wrote unit tests for existing Django-based REST APIs, improving code reliability and reducing production bugs by 15%.
• Set up and managed an ELK stack for machine metrics and custom application logs, improving real-time monitoring and incident response times.
• Migrated model training from R to Python, reducing processing time and simplifying code maintenance.

Aug 2017 – Jun 2018 · 10 mos

Aug 2013 – Jun 2014 · 10 mos · IIT-Bombay

• Was a part of a team where we developed an autonomous underwater vehicle which localizes itself and performs realistic missions based on feedback from visual, inertial, acoustic and depth sensors using thrusters and pneumatic actuators.