Vetted BigQuery Professionals

“Applied Scientist with legal-tech experience who builds production LLM systems. Created and deployed Quibo AI, a LangGraph-based multi-agent pipeline that turns large markdown/Jupyter inputs into polished blogs and social posts, overcoming context limits via ChromaDB + HyDE RAG. Also built a large-scale iterative code-evolution workflow using multi-model orchestration (GPT/Claude/Gemini) with testing, debugging loops, and evaluation/observability practices.”

“Growth creative lead at Amazon who ran structured, incrementality-informed A/B tests for Prime acquisition on Amazon DSP. Produced a winning benefit-led video + social-proof framework that improved CTR/CVR while cutting CPA (-24%) and increasing ROAS (+32%), then scaled the approach across email and onsite placements for an additional 10–12% lift in Prime sign-ups.”

“Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.”

Tom Dinwiddie

Screened

Executive IT Leader specializing in global SaaS, cloud transformation, and M&A integration

20y exp

“Technology executive/CTO-type leader with experience at ALLDATA defining and operationalizing an executive-prioritized roadmap, scaling distributed engineering teams (including expansion in Mexico and India), and modernizing products onto a containerized Google Cloud architecture. Highlights include 99.96% reliability, 38% maintenance cost reduction, and strong security/compliance posture (CyberArk, ISO27001, SOC2, SOX).”

“Primary engineer at Customer Insights AI who built an end-to-end Python pipeline for 340B drug pricing compliance, using ML to detect suspicious pharmaceutical claims and benefit diversion. Stands out for combining healthcare compliance domain knowledge with production reliability practices, and for turning ambiguous analyst-driven review processes into automated workflows that cut manual review by 70%.”

“Internship experience at TikTok and nCino, with hands-on work spanning production Python data pipelines, recommendation-system feature workflows, Salesforce Apex automation, and flaky UI automation for a live stock recommendation platform. Stands out for a reliability-focused approach: anticipating failure modes, instrumenting observability, and turning ambiguous business processes into maintainable automated systems.”