Vetted Snowflake Professionals

“Early-stage founder building a service business targeting small clinics, already with one client. Identified the opportunity by helping a family member and then validating needs through direct client conversations; uses AI (including AI agents) for content generation and plans deeper workflow automation to scale cost-effectively.”

Brian Gomez

Screened

Senior Machine Learning Engineer specializing in AI/ML, NLP, and computer vision

United States12y exp

“McKinsey & Company ML/NLP practitioner who builds production-grade AI systems across sectors (notably healthcare and finance), including RAG/LLM solutions, entity resolution pipelines, and embedding-powered search with vector databases. Demonstrated measurable impact (40% reduction in data duplication) and strong MLOps/data workflow practices (Airflow, MLflow, Spark, AWS/GCP, Prometheus, CI/CD).”

“Financial engineering analyst at BlackRock who has built internal data products for thousands of sales users, including an end-to-end fund comparison system that combines internal and third-party data into compliance-approved PDFs. Brings a mix of data engineering, stakeholder-heavy delivery, and emerging AI experimentation, with current work focused on regression testing and Snowflake-based portfolio data automation.”

“Backend/data engineer with production experience at Uber building a near real-time driver rewards service on AWS (FastAPI, PostgreSQL, Redis) with strong reliability and concurrency controls. Also delivered AWS Lambda/ECS containerized deployments with GitHub Actions CI/CD and cost governance, built AWS Glue ETL with schema-evolution handling, and drove a ~10x SQL performance improvement while owning incident response via CloudWatch.”

Sri Yogesh Dorbala

Screened

Engineering Manager / Tech Lead specializing in large-scale distributed systems

Seattle, WA8y exp

“Software engineer focused on personalization and data/ML infrastructure who built a GenAI/LLM-driven carousel ranking system end-to-end, delivering a reported 6–7% order-rate lift. Also designed large-scale personalization ETL (15PB for ~100M users) and created a custom Airflow operator to integrate with Databricks under enterprise version constraints, with hands-on on-call and data-quality reliability improvements.”

“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”

“Repeat startup co-founder with multiple successful exits and significant fundraising experience (most recent raise $6M USD; prior raise £10M GBP). Interested in roles bridging investors and startups—performing due diligence and evaluating MVPs/USPs to help firms invest in the right companies and support portfolio growth toward exit.”

“Senior product engineering and data architecture leader who has owned end-to-end solutions for enterprise analytics and legal search platforms, including work for Sony Pictures Entertainment and Accenture Legal. Combines executive-level architecture and team leadership with hands-on experimentation in modern AI systems, recently building a multimodal Hugging Face agent that significantly exceeded its benchmark score.”