Myrza Nurmanbetov

Led design and delivery of AWS Lambda-based Python data pipelines processing 500GB+

• • datasets, enabling near real-time analytics for a platform serving 1M+ users. Scaled distributed data workflows by integrating AWS Neptune, DynamoDB, and Lambda, enabling complex graph queries and improving large dataset processing performance. Built and owned 10+ Django microservices supporting frontend applications and handling 200k+ API requests per day. Reduced deployment time from 2 hours to under 5 minutes by implementing containerized CI/ CD pipelines using Docker and automated release workflows. Reduced production downtime by 24% by introducing improved monitoring and alerting using CloudWatch and Prometheus. Delivered backend AI processing pipelines integrating image enhancement services and scalable cloud storage workflows. Mentored junior engineers and reviewed backend architecture proposals, improving engineering consistency and service reliability.

Developed and maintained HIPAA-compliant REST APIs using Django REST Framework

• • supporting 1 M+ patient records. Improved platform reliability by 25% by refactoring legacy Python services and optimizing backend architecture. Reduced search latency from ~900ms to ~250ms by implementing and tuning Elasticsearch infrastructure. Owned multiple backend services across the SDLC, including architecture design, deployment automation, and operational monitoring. Diagnosed and resolved Elasticsearch indexing and mapping issues, stabilizing search functionality for production workloads. Automated data enrichment workflows by implementing AI-assisted backend processing pipelines.

Built scalable Flask-based REST APIs supporting internal data ingestion and transformation

• • pipelines. Implemented secure authentication systems using JWT and OAuth with role-based access control. Automated operational reporting workflows, reducing manual reporting time through Python analytics pipelines. Containerized backend services with Docker and deployed to AWS and Heroku, improving environment consistency and deployment reliability.