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Vetted Snowflake Professionals
Pre-screened and vetted.
Mid-level Data Engineer specializing in cloud-native batch and streaming pipelines
Intern software engineer specializing in AI, data science, and full-stack development
kireeti Sangarsh
Mid-level Data Engineer specializing in cloud ELT pipelines and analytics engineering
“Data engineer who has owned end-to-end ELT pipelines on Airflow + AWS (S3/Glue/Lambda) with Snowflake/Redshift, processing millions of records per day and tens of GBs via PySpark. Built strong data quality and reliability practices (40% quality improvement, 99%+ uptime), and also designed a resilient web-scraping system with anti-bot defenses and schema-change versioning plus REST APIs for serving curated data.”
namratha sai
Junior Healthcare Data Analyst specializing in clinical data validation and EHR/claims analytics
“QA/supplier-performance focused candidate who uses defect and delivery data to spot recurring issues early, identify root causes tied to rushed timelines/high workload, and implement practical process changes (e.g., added validation steps and tightened defect definitions). Emphasizes clear, metric-backed communication to align internal stakeholders and suppliers, then monitors post-change results to confirm sustained improvement.”
Rutu Ketankumar Shah
Mid-level Software Engineer specializing in AI automation and backend systems
“Hands-on automation and QA-focused developer using AI agents, MCP tools, and LLMs to streamline business workflows. Built agents for automated Jira bug logging, executive summary dashboards, and a rule-explainer that translates technical business rules into plain language for end users, while also supporting Selenium-to-Playwright migration and guiding peers on AI implementation.”
Ricky Zheng
Senior Backend/AI Engineer specializing in AWS-native data processing and legacy modernization
“Backend/data engineer with hands-on production experience building a FastAPI Python service on AWS for real-time AI workflows (Postgres/Redis, containers behind API Gateway) with strong reliability practices (JWT auth, timeouts/retries, health checks). Has delivered AWS infrastructure using Terraform + GitHub Actions across environments, built Glue ETL pipelines into Snowflake with idempotent recovery, and modernized legacy batch workflows via parallel-run parity validation and phased cutovers.”
Entry-Level Full-Stack AI Engineer specializing in RAG pipelines and enterprise SaaS
Junior Full-Stack Software Developer specializing in cloud-native apps and data/AI
Mid-level R&D Engineer specializing in applied AI, experimentation, and cloud-integrated prototypes
Mid-level Data Analyst specializing in marketing and product analytics
Senior Full-Stack Engineer specializing in Python, data platforms, and cloud systems
Mid-level Machine Learning Engineer specializing in Generative AI and healthcare NLP
Mike Fernandez
Mid-Level Software Engineer specializing in cloud data platforms and CI/CD
“AI/LLM engineer who has owned end-to-end production delivery of multi-agent RAG systems on Azure (React + FastAPI + data pipelines + Terraform), including rigorous evaluation/monitoring and reliability guardrails. Shipped an AI-driven observability root-cause analysis assistant that reduced MTTR ~30%, cut alert noise ~20%, and reached ~70% adoption in the first month; also built a clinical document Q&A system with citations and compliance-oriented controls.”