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Vetted SQL Query Optimization Professionals
Pre-screened and vetted.
“Built and operated end-to-end legal-document data pipelines fed by hundreds of scraper sources, emphasizing data quality validation, reliability (CloudWatch monitoring/alerting, retries, backfills), and serving enriched legal data via serverless AWS APIs (Lambda/API Gateway). Experienced in keeping API contracts stable with additive versioning practices and shipping MVPs quickly with CI/CD and observability in place.”
Vincent Dory
Senior Python Full-Stack Engineer specializing in AWS media processing platforms
“Lead developer on a Warner Brothers Discovery media management platform, building Python/Flask APIs and AWS-based workflows. Delivered a serverless search overhaul (Lambda + API Gateway + OpenSearch Serverless) while maintaining parity with legacy Rekognition tag-based search, and implemented event-driven ETL (SNS/SQS) to ingest/validate CSV metadata into PostgreSQL with strong logging and incident response practices.”
Thanuja Mudududla
Mid-level Software Engineer specializing in full-stack cloud and agentic AI systems
“Backend engineer with hands-on ownership of production systems across maritime tracking, HR tech, and AI-powered document workflows. They combine strong operational instincts with measurable impact—cutting API latency from 10s to 3s, improving query performance by 60%, reducing deployment time by 50%, and driving 70% infrastructure cost savings with serverless design.”
Shubh Dholakiya
Mid-Level Full-Stack Software Developer specializing in Java/Spring microservices and cloud
“Backend engineer who owned and shipped a campaign analytics API (FastAPI/Postgres/Redis/Celery) with ingestion from Instagram/YouTube, JWT auth, tests, and Docker deployment; improved performance from >1s to <150ms using precomputed aggregates and composite indexes. Experienced with Kubernetes GitOps using GitHub Actions + ArgoCD (zero-downtime rollouts, one-click rollbacks), Prometheus/Grafana observability, hybrid cloud-to-on-prem migrations, and real-time notification streaming via Redis Pub/Sub + WebSockets.”
Shravan Yadav
Mid-level Software Engineer specializing in cloud and FinTech systems
“Backend/AI engineer who has built and operated production Node.js/Express services on AWS (Postgres/Redis) and has hands-on experience shipping an AI-powered support agent using RAG (Pinecone + LLM) with grounding checks and evaluation for hallucination rate. Demonstrates strong production reliability/performance debugging, including reducing peak latency from ~2s back to sub-300ms through query and caching optimizations, plus designing agent workflows with retries and human-in-the-loop escalation.”
Mid-Level Full-Stack Product Engineer specializing in Next.js, React, and Postgres
Junior Full-Stack Software Engineer specializing in Node.js, Django, and cloud microservices
Junior Cloud Software Engineer specializing in AWS serverless and data platforms
Junior Full-Stack Software Engineer specializing in cloud-native microservices and data platforms
Mid-level Full-Stack Developer specializing in Java/Spring Boot, React/Angular, and cloud microservices
Senior Software Engineer specializing in AWS serverless, APIs, and data/ETL platforms
Mid-level Cloud Data Engineer specializing in multi-cloud data platforms and analytics
Mid-level Full-Stack Software Engineer specializing in cloud microservices and ML integration
Mid-Level Full-Stack Developer specializing in Java/Spring and React for enterprise SaaS
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
Mid-level Full-Stack Java Developer specializing in FinTech and cloud microservices
Mid-level Backend/Full-Stack Software Engineer specializing in cloud-native microservices
Senior Full-Stack Software Engineer specializing in AWS, .NET, and data/telemetry platforms
Mid-level Software Engineer specializing in backend APIs and React full-stack development
Mid-level Data Engineer specializing in FinTech and AI-ready data platforms
Himanshu Kiran Garud
Mid-Level Software Engineer specializing in full-stack web and data engineering
“Backend/ML engineer who has built both enterprise data pipelines and real-time AI products: modular Python (Flask/FastAPI) services integrating automation scripts and low-latency ML inference (MediaPipe, PyTorch) plus OpenAI-powered feedback. Demonstrated measurable performance wins (~30% faster HR workflows; ~40% faster AWS pipelines across 100+ Oscar Health feeds) and strong multi-tenant/data-isolation patterns (schema-based isolation, RBAC, microservices).”