Mid-Level Backend Engineer specializing in AWS serverless and data processing
Software Development Engineer II7 years experienceMid-LevelMedia & EntertainmentStreaming MediaE-commerce
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About
Amazon Prime Video backend engineer who built and operated high-traffic Python/FastAPI services and AWS-native data/batch systems. Demonstrates strong production reliability and incident ownership (CloudWatch/X-Ray), plus measurable performance wins (8s to <200ms query latency, ~40% CPU reduction) and cost-focused architectures (Lambda + ECS/Fargate with Fargate Spot).
University of California, Irvinebachelor, Computer Engineering (2018)
Key Strengths
Built high-scale Python/FastAPI services handling thousands of concurrent I/O requests
Strong security/auth design using AWS SigV4 with request interception and IAM principal validation
Reliability engineering: retries/timeouts with Tenacity (exponential backoff + jitter) and fail-fast error handling
Delivered hybrid serverless + containers architecture (Lambda orchestration + ECS/Fargate for heavy processing) with IaC and blue-green CI/CD
Cost optimization using Fargate Spot (reported up to ~70% savings) and autoscaling via ECS target tracking
Designed AWS Glue ETL from S3 telemetry to partitioned Parquet with schema evolution via Crawlers/Data Catalog and data quality checks
Built resilient batch recovery using Step Functions + Lambda log inspection and Glue Bookmarks to avoid reprocessing
Modernized legacy monolith/stored-procedure system into Python microservices with canary rollout (5% increments) and parity reporting
SQL performance optimization with measured impact: reduced query latency from ~8s to <200ms and cut CPU ~40%
Incident ownership: detected batch stall via CloudWatch alarm, triaged with Logs/X-Ray, mitigated via caching and catch-up job, prevented recurrence by decoupling with SQS + Lambda
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