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Backend Developer with Internships at Floww.ai and StressAway
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Competencies
Proficient in designing scalable, secure backend systems using Python, FastAPI, and Django.
Experienced in creating and documenting RESTful APIs with OpenAPI/Swagger standards.
Skilled in Docker, container orchestration, and implementing structured logging for improved observability.
Capable of integrating frontend and backend components using React.js, Node.js, and related technologies.
Education
Summary
Dedicated backend developer skilled in Python, API design, containerization, and full-stack integration. Proven track record in enhancing system stability, security, and user experience through innovative solutions and collaborative projects.
Key Achievements
- Engineered persistent Docker-based logging, enhancing observability and eliminating container log loss.
- Developed IAM Teams module with RBAC, hierarchical permissions, and multi-tenant support for multiple enterprise clients.
- Reduced onboarding drop-off by 25% through OAuth 2.0 integration and scalable API development.
Experience
Open Source Contributor
Eliminated container log loss by engineering persistent Docker-based logging via shared volumes across restarts and rebuilds; improved observability using structured log aggregation.. Cut migration risk by 60% via a PoC for moving team communications from MostlyMatter to Mattermost, covering integrations, security, and edge cases.. Reduced CI pipeline failure noise by 40% by introducing GitLab CI with automated linting, SAST (SonarQube), Snyk dependency scans, and build checks; enforced branch protection and merge request gates.. Enforced 100% pre-commit compliance by standardizing formatting, linting, and security validation gates across the engineering team; improved code quality and reduced review overhead.
Backend Developer Intern (Top Performer)
Engineered IAM Teams module with role-based access control (RBAC), hierarchical permissions, and multi-tenant isolation for 3+ enterprise tenants; documented APIs via OpenAPI/Swagger.. Cut analytics latency from 2 hours to 15 minutes (87.5% reduction) by re-architecting the ETL pipeline from RDS to Amazon Redshift; implemented star schema data modeling and query optimization via indexing and partitioning.. Boosted category query performance 3× via a deep-nested hierarchical category system; added Redis caching layer to reduce repeated DB round-trips and improve API response times.
Full-Stack Developer Intern
Reduced onboarding drop-off by 25% by integrating OAuth 2.0 authentication and scalable RESTful APIs with rate limiting, improving backend stability, security, and user flow.