Responsibilities

• Architect scalable backend services using FastAPI, Django, and PostgreSQL.
• Lead backend initiatives, enforcing clean code and best practices.
• Mentor engineers through code reviews and technical workshops.
• Drive CI/CD, containerization, and infrastructure automation.
• Ensure security compliance and optimize performance.

Achievements

• Boosted application performance by 40% via backend optimizations.
• Led a team of 5 on high-impact projects, achieving on-time delivery.
• Reduced deployment time by 60% with Docker and GitHub Actions CI/CD.
• Built RESTful APIs handling 1M+ daily requests with 99.9% uptime.
• Migrated monolith to microservices, cutting downtime by 70%.
• Enhanced response time consistency by 35% with profiling tools.
• Improved throughput by 50% using asynchronous FastAPI programming.
• Implemented observability (Prometheus, Grafana, Sentry), reducing MTTR by 40%.

Projects

• CardTrack Engine : Developed image-based search system for collectible cards using FastAPI, CLIP embeddings, and vector search, handling 1M+ records with real-time responses.
• CI/CD Overhaul : Redesigned deployment pipelines with Docker and GitHub Actions for zero-downtime blue-green deployments.
• Monolith to Microservices : Led migration of Django monolith to FastAPI/gRPC microservices, improving modularity and performance.

Impact and Outcomes

• Cut incident recovery time from 2 hours to 40 minutes with observability tools.
• Reduced onboarding time from 3 weeks to 1 week via automation.
• Increased delivery velocity by 30% through DevOps automation.

Tools and Platforms

Technologies Used

Responsibilities

• Developed backend services for automated coupon scraping using Python and headless browser automation.
• Built a Chrome extension for real-time coupon application during checkout on supported e-commerce sites.
• Collaborated closely with QA and frontend teams to maintain high product standards.
• Integrated logging and monitoring tools to track scraping success and coupon validity.
• Maintained and extended scraping rules to adapt to site structure changes.

Achievements

• Increased scraping accuracy by 45% through improved DOM targeting and error handling.
• Boosted scraping speed by 60% with concurrent task execution and request optimizations.
• Contributed to a Chrome extension that reached 5K+ active users within 2 months.
• Reduced manual QA efforts by 70% via automated test scripts and monitoring dashboards.

Projects

• Coupon Scraper Engine : Designed a robust scraping pipeline using Python and Puppeteer for extracting and validating coupons from 100+ e-commerce websites.
• Smart Apply Extension : Built and maintained a Chrome extension that automatically detects and applies best coupons at checkout, enhancing UX and driving user retention.
• QA Automation Suite : Implemented automated test cases and monitoring scripts to ensure scraper and extension stability across updates.

Impact and Outcomes

• Reduced coupon discovery and application time by over 80%, improving user satisfaction.
• Enhanced customer retention and checkout conversion through automated savings features.
• Improved system resilience to layout changes via flexible selector strategies and fallback mechanisms.

Tools and Platforms

Technologies Used

Responsibilities

• Translated complex business requirements into actionable technical tasks.
• Developed high-performance, RESTful APIs using FastAPI and Flask.
• Maintained effective communication across sales, marketing, and development teams.
• Collaborated with DevOps to deploy services and monitor system performance on AWS.
• Assisted in logging and tracing service behavior via Elastic Stack (ELK).

Achievements

• Accelerated backend development timelines by 30% through improved coordination.
• Reduced communication gaps between business and tech teams by establishing standardized documentation practices.
• Increased system visibility with integrated logging and monitoring using ELK.
• Delivered stable and well-documented APIs that reduced frontend-backend friction.

Projects

• Business Requirement Mapping Tool : Built internal tooling to convert client requirements into structured engineering tasks, improving backlog clarity and team efficiency.
• API Development Stack : Implemented robust API services using FastAPI and Flask for internal business operations, enabling faster product iteration.
• AWS Deployment & Monitoring : Worked with infrastructure team to containerize services, deploy them on AWS, and set up real-time monitoring using the Elastic Stack.

Impact and Outcomes

• Improved alignment between product vision and technical implementation.
• Reduced production incidents through proactive monitoring setup.
• Enabled quicker stakeholder feedback loops by reducing technical iteration cycles.

Tools and Platforms

Technologies Used

Responsibilities

• Built data pipelines for extracting and processing employee performance metrics.
• Integrated ML-driven logic to generate tailored feedback based on historical work data.
• Optimized PostgreSQL queries and schema for faster access and lower latency.
• Implemented Redis caching to reduce DB read load and improve API response times.
• Deployed backend services on AWS, including EC2 for compute and S3 for data storage.

Achievements

• Reduced database load by 30% through caching, indexing, and query optimization.
• Enabled personalized employee feedback via automated ML-based analysis.
• Deployed and maintained reliable cloud infrastructure with 99.9% uptime.
• Streamlined processing of large employee datasets with minimal performance bottlenecks.

Projects

• ML-Powered Review Engine : Engineered a backend system to support a machine learning pipeline for generating automated performance feedback for employees.
• Database Optimization Layer : Improved database performance with strategic indexing, optimized query plans, and Redis-based caching.
• Cloud Infrastructure Deployment : Set up scalable infrastructure using AWS EC2 and S3 to ensure reliable and cost-efficient application hosting.

Impact and Outcomes

• Improved system responsiveness and scalability, enhancing user experience.
• Enabled faster and more accurate performance reviews through ML integration.
• Reduced operational overhead by automating infrastructure setup and tuning.

Tools and Platforms

Technologies Used

Responsibilities

• Developed backend logic for interactive web applications using Django and Django REST Framework.
• Created REST APIs to expose monitoring data for frontend visualization tools.
• Built an intuitive frontend interface to display database metrics and real-time system information.
• Implemented a high-performance real-time filtering and visualization engine to handle millions of records efficiently.
• Collaborated with UI/UX and product teams to improve accessibility for non-technical stakeholders.

Achievements

• Improved monitoring system functionality by integrating new backend features and APIs.
• Reduced query response time by 45% with efficient filtering and indexing strategies.
• Increased stakeholder engagement by 60% through enhanced data visibility.
• Successfully scaled data visualization system to handle millions of records with low memory overhead.

Projects

• Monitoring Dashboard Backend : Designed Django-based backend system and APIs to support a live monitoring dashboard with robust data querying and filtering capabilities.
• Real-Time Visualization Engine : Engineered a high-performance data pipeline and visualization interface to support millions of records in real-time.
• Stakeholder Web Interface : Built a user-centric frontend connected to REST APIs for real-time data inspection and decision-making.

Impact and Outcomes

• Enhanced system observability and responsiveness for internal and external users.
• Increased transparency and usability of critical system metrics across departments.
• Boosted development velocity by streamlining API contracts and frontend/backend integration.

Tools and Platforms

Technologies Used