Sr Fullstack Developer | Expert in Python, Java | AI specialist | VectorDB
Senior Python Backend Developer with 10+ years building scalable, data-driven systems. Expert in Django, Flask, REST APIs, and microservices. Strong experience with AWS (S3, Lambda, EC2), MongoDB, DynamoDB, and... More
[Python APIs & AWS Integration] Implemented data-driven APIs using Python/Flask integrated with AWS S3 and DynamoDB, optimizing data retrieval for compliance queries, resulting in 30% reduction in processing time for millions of daily transactions. [Microservices Optimization] Developed scalable microservices with MongoDB for analytics log storage, applying fault tolerance and performance tuning, resulting in enhanced resilience in high-load environments akin to AdTech systems. [Code Reviews & Collaboration] Participated in design discussions and code reviews with data engineering teams, improving API documentation and external integrations, resulting in smoother deployments and 25% bug reduction.
[Data-Driven Services in Python] Designed backend services in Python/Django with Kafka and PostgreSQL for fraud pipelines, integrating AWS S3 for event storage, resulting in 42% reduction in error rates for large-scale transaction volumes. [NoSQL & Scalability] Built data retrieval using Redis and MongoDB in microservices, optimizing for sub-50ms queries, resulting in improved fault tolerance in high-load financial data systems. [API Design & Integration] Developed RESTful data-driven APIs connecting internal/external systems via Lambda, contributing to system improvements, resulting in more efficient and scalable analytics integrations.
[Backend Services & DynamoDB] Created Python/Flask services with DynamoDB for data storage during monolith-to-microservices migrations, optimizing scalability and performance, resulting in 30% throughput increase for high-load applications. [Database Optimization] Worked with MongoDB and SQL for data retrieval and modeling in APIs, applying debugging for fault tolerance, resulting in more robust data-driven integrations. [AWS & Collaboration] Integrated AWS EC2 and S3 into Python pipelines, participating in design discussions with teams, resulting in collaborative deployments and improvements in data integration patterns.
Emphasis on data modeling and complex analysis, applied to Python backend and AdTech data patterns.
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