Vetted SQL Professionals

“Worked on an AWS DynamoDB Journal team project building internal operator dashboards end-to-end, creating Java/Spring Boot APIs and integrating them into a Spring Boot/Thymeleaf/JavaScript UI to speed up debugging workflows. Has experience with data-heavy web apps and performance techniques (load balancing, caching, pagination, compression) plus hands-on debugging across unit/integration/E2E tests; also maintained and enhanced a React website at Global Spark.”

Ridhi Singhal

Screened ReferencesStrong rec.

Mid-level strategy and analytics professional specializing in growth and due diligence

Atlanta, GA4y exp

“Growth and launch operator with Uber experience spanning marketplace expansion, rider/driver activation, and scalable onboarding systems in new-city launches, including Uber Shuttle in India. Stands out for combining data analysis, operational modeling, and cross-functional experimentation to unlock incremental revenue, improve NPS, and build repeatable playbooks that scaled across markets.”

Tolulope Akinlabi

Screened ReferencesStrong rec.

Mid-level Cyber & Cloud Security Analyst specializing in AI/ML and cloud risk

Lanham, MD6y exp

“Built a production AI security compliance assessment system using the OpenAI API that ingests company policy documents, performs RAG over embeddings stored in Supabase/FAISS, and generates executive-level gap and maturity reports mapped to NIST CSF, SOC 2, and PCI DSS. Also developed a multi-agent trading assistant orchestrated with LangChain, combining live market data (Yahoo/Polygon.io), sentiment/technical indicators, LSTM-based forecasting, and LLM-generated recommendations.”

“Built end-to-end AI analytics experiences spanning React/TypeScript, serverless APIs, and Postgres, with a strong focus on streaming UX, observability, and reliability. Stands out for turning ambiguous AI product ideas into shippable MVPs, then abstracting repeated patterns into reusable orchestration and multi-tenant configuration systems that improved speed, consistency, and maintainability.”

“Google Health engineer who owned and shipped an AI-powered clinical insights dashboard and NLP clinical note extraction service end-to-end (React/Next.js frontend; Python/Node microservices on GKE; TensorFlow transformers; BigQuery analytics). Demonstrated strong production rigor (CI/CD, testing, observability, guardrails for sensitive data) and delivered measurable outcomes including 30% faster diagnostics, 40% less manual documentation, 15% higher adoption, and 25% lower ops costs.”