Vetted Database Schema Design Professionals

“Backend engineer with experience modernizing a large-scale procurement platform at Jio Platforms by breaking a monolith serving 35 business units into Spring Boot microservices, improving uptime and cutting report latency ~30%. Also built high-concurrency FastAPI systems (200ms at ~500 concurrent users) with strong security (JWT/OAuth2/RBAC), event-driven Kafka integrations, and reliability patterns like exactly-once delivery for ~1M monthly triggers.”

“Senior engineering manager who stays hands-on (~50/50) while leading teams through design reviews, code reviews, and production issue triage. Shipped scalable platform features (notifications, user action tracking via microservices) with strong quality/performance practices (TDD, high-load testing). Owned a complex cross-system SSO/IdP incident end-to-end, identifying a SameSite+iFrame root cause and delivering a configurable product fix plus support documentation.”

“Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.”

“Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.”

“Product-focused full-stack engineer at startup (Zippy) who shipped a production multi-agent AI system for restaurant operations plus payments workflows. Built end-to-end: RAG grounded on a Notion knowledge base, structured function-calling task routing, FastAPI/JWT multi-tenant backend, and a polished React+TypeScript owner dashboard. Has real production incident experience (duplicate Stripe webhooks) and reports ~94% task-routing accuracy under load.”

“Software engineer with strong full-stack and platform experience (TypeScript/React/Node.js) who has built real-time analytics dashboards and microservices using RabbitMQ. Demonstrates production-minded decision-making under launch pressure (manual fallback for payment-impacting third-party API issues) and has delivered internal DevOps tooling that automates compliance checks via GitHub/Jira integrations.”

“Backend engineer who led major modernization efforts at GoDaddy, migrating legacy Perl services to Python/FastAPI with an incremental rollout strategy, containerization (Docker/Kubernetes), and CI/CD (Jenkins/GitHub Actions). Strong focus on secure, reliable API design (JWT, RBAC, PostgreSQL row-level security), rigorous testing, and data integrity—plus experience hardening an automated web-scraping pipeline against changing site structures and downtime.”

“Cofounded a travel app and built a production place recommendation + review system end-to-end using Next.js App Router and TypeScript, including Postgres-backed APIs and post-launch monitoring. Uses structured logging with Sentry and Vercel Analytics to diagnose issues and validate performance improvements, and has some exposure to Temporal-based workflow orchestration with retries/idempotency.”

“Built an AI basketball shooting coach that analyzes player form against NBA players and recruited 30+ beta users via Reddit to drive iterative UI/workflow improvements. Also has internship experience building an administrative server and coordinating API/database compatibility with another client server, emphasizing communication and integration quality.”

“Full-stack engineer with experience building secure, cloud-native document/workflow platforms handling high-volume customer and medical data across microservices on Kubernetes. Demonstrated impact improving performance via event-driven AWS architectures (Lambda + DynamoDB Streams) and strengthening compliance/security for S3-stored documents using IAM and KMS. Has delivered end-to-end APIs and UIs using Java/Spring Boot with Angular/React, plus Docker and CI/CD.”

“Full-stack engineer who built and owned a generative-AI pipeline end-to-end inside the Vibecut video editor using Next.js App Router/TypeScript, Gemini-based prompt routing, and Zustand state management, including concurrency-safe requests. Also integrated Python services to access newly released AI tooling, optimized Postgres/S3 data flows for thumbnails, and built Modal-to-Amplitude workflows for Reddit-driven sentiment/metrics in a pre-seed environment while also handling marketing.”

“Software engineer with hands-on ownership of both fintech checkout improvements (saved payment methods/one-click checkout with tokenization and feature-flag rollouts) and production LLM/RAG systems for customer support. Demonstrates strong operational rigor via guardrails, evaluation loops integrated into CI/CD, and scalable data pipelines handling messy PDFs/CSVs/logs with reliability and observability.”

“Backend/distributed-systems engineer who built a Golang distributed key-value store on AWS using Multi-Paxos, WAL, and non-blocking gRPC replication (cutting write latency ~40%) and proactively addressed tricky failure modes like leader-election livelock. Also developed a Python/Kubernetes cost-optimization scaling engine deployed with Helm/Terraform, delivering ~$40K annual savings while sustaining 99.99% uptime, and drives contract-first API development (OpenAPI/Swagger) to speed frontend integration.”

“Backend engineer with TaskRabbit experience building and operating payment/booking services in Python/Django on AWS (ECS + Lambda) with Kafka/SQS eventing. Demonstrates strong production reliability and incident ownership in high-stakes payment flows (idempotency, strict timeouts, retries, monitoring/alerting) plus data/ETL work in AWS Glue and measurable SQL performance wins.”

“Backend/platform engineer who has owned a real-time business analytics dashboard backend (Python/Flask/MongoDB) and built Kafka event-streaming pipelines with idempotent processing and DLQs. Strong DevOps/GitOps experience deploying containerized microservices to AWS EKS with CI/CD (Jenkins/GitHub Actions/CodePipeline) and ArgoCD auto-sync/drift detection, plus hands-on support for phased hybrid cloud/on-prem migrations using feature flags and replication.”

“Backend engineer focused on scalable Python/Flask services and high-performance PostgreSQL/SQLAlchemy systems, with demonstrated wins like reducing N+1-driven response times to under 200ms and cutting P95 latency below 1s via background queues and caching. Has production experience operationalizing ML models as Dockerized APIs on AWS (S3/Lambda) with monitoring (CloudWatch/ELK), plus robust multi-tenant isolation using JWT-driven tenant context and row-level security.”

“Forward Deployed Engineer focused on taking enterprise LLM voice agents from prototype to production. Led a turnaround on a high churn-risk account by building a custom nested-API integration and preprocessing layer that enabled the LLM to reason over complex order hierarchies, cutting call handle time from 15 minutes to 2 minutes and driving expansions. Strong in real-time agent/workflow debugging, developer workshops, and sales partnership for adoption.”

“Full-stack engineer who built and owned an AI-powered personal statement editor in Next.js (App Router + TypeScript), including dynamic routing, server-side data fetching, and typed API route handlers. Post-launch, they handled production monitoring/debugging and shipped reliability/performance upgrades (rate limiting, retries, rollback, DB indexing), and report a 40% latency reduction using Suspense/streaming and React concurrency patterns. Also implemented a durable Temporal-orchestrated AI document workflow with robust retry/idempotency strategies.”

“Frontend engineer who has led end-to-end delivery of both an open-source JavaScript document-comparison library and complex React+TypeScript product features (e.g., Google-Drive-like auto-save with S3 persistence). Demonstrates strong architecture and performance instincts (Redux/hooks patterns, dynamic loading to improve Lighthouse scores) and pragmatic shipping/rollout skills including cross-browser mitigation with feature flags.”

“Built and deployed a compliance-sensitive LLM pipeline that extracts rebate logic from hospital–supplier medical contracts, using multi-layer redaction (regex/NER/dictionary), schema-validated structured outputs, and secure placeholder reinsertion. Hosted models on Amazon Bedrock to avoid retraining on sensitive data and improved both accuracy and cost by splitting the workflow into a lightweight section classifier plus a fine-tuned extraction model, orchestrated with LangChain and evaluated via layered, test-driven agent assessments.”

“Backend engineer who built an async FastAPI data pipeline at GHN Career Academy to replace a manual Excel-based workflow, migrating 30k+ contact records into Airtable with validation/deduplication and best-effort GPT-based enrichment. Emphasizes reliability under messy real-world data and partial failures via structured logging, retries, and resumable processing, unlocking downstream automations (e.g., Zapier and chatbots).”

“Backend/platform engineer who owned a real-time customer analytics microservice stack in Python/FastAPI with Kafka streaming into PostgreSQL, including schema enforcement (Avro) and high-throughput optimizations. Strong Kubernetes + GitOps practitioner (EKS/GKE, Helm, Argo CD) who has handled CI/CD reliability issues with automated pre-deploy checks and rollbacks, and supported major migrations (on-prem to AWS; VM to EKS) with blue-green cutover planning.”

“Backend engineer with Citi Bank experience building and operating a Python/Flask Personal Finance Manager platform at 1M+ transactions/month. Strong in secure API design, database performance tuning (PostgreSQL/Azure SQL), and production reliability (92%+ test coverage, load testing, monitoring). Also integrated an NLP expense-tagging microservice with caching, background workers, autoscaling, and multi-tenant isolation via RLS and tenant-aware JWT.”