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Vetted ELT (Extract, Load, Transform) Professionals
Pre-screened and vetted.
sandeep Barige
Intern AI/ML Software Engineer specializing in LLMs, NLP, and multimodal systems
“Built and deployed a production AI-powered personalized learning platform (Django + FastAPI) featuring an LLM+RAG tutoring assistant and automated grading. Demonstrates strong applied LLM reliability engineering (structured JSON outputs with Pydantic validation, hallucination control via FAISS-based RAG thresholds and refusals) plus scalable async microservice design and Airflow-orchestrated ETL across AWS/GCP.”
Charmi Dharmendrakumar Parmar
Mid-Level Software Engineer specializing in full-stack and cloud-native systems
“Backend/full-stack engineer who owned a cloud-native, AWS-based microservices backend for an HRIS product used by ~10,000 users, including onboarding and workflow orchestration. Strong production focus on event-driven architecture, idempotency/retries, observability, and developer-friendly API design (OpenAPI, versioning, JWT), plus hands-on Selenium automation for resilient checkout-style flows.”
Joseph Heaney
Mid-level Data Engineer specializing in ETL pipelines, BI, and cloud data platforms
“Data- and backend-leaning full-stack candidate with hands-on experience building Python ETL pipelines, complex SQL reporting, and Power BI infrastructure at Eastman. They improved internal operations by consolidating a multi-sheet task workflow into a simpler automated system and have repeatedly delivered reporting solutions by iterating directly with business stakeholders under ambiguous requirements.”
Matt Leger
Executive Technology Leader specializing in SaaS, cloud, data, and AI platforms
“Seasoned engineering leader and Fractional CTO with 20+ years of experience helping startups navigate the transition from early product traction to scalable operations. Particularly strong in stepping into VC-backed, high-growth environments, stabilizing fragile MVP-era systems, and aligning technology strategy with business, operational, and fundraising goals.”
Junior AI Engineer specializing in LLM agents, RAG, and MLOps
Senior AI/ML Engineer specializing in Generative AI, NLP, and MLOps
Senior DevOps Engineer specializing in multi-cloud infrastructure and data pipelines
Mid-Level Software Engineer specializing in full-stack development and data/ML systems
Senior Full-Stack Software Engineer specializing in eCommerce and cloud integrations
Mid-level Software Engineer specializing in AWS, Python, and RAG-based LLM systems
Mid-level Full-Stack Software Engineer specializing in Java/Spring and AWS serverless
Mid-level Supply Chain Analyst specializing in forecasting, ETL, and BI dashboards
Mid-level Data Engineer specializing in cloud data platforms and streaming analytics
Mid-level Machine Learning Engineer specializing in NLP, Computer Vision, and LLMs
Mid-level Data Engineer specializing in large-scale pipelines and LLM-based metadata enrichment
Senior Backend Engineer specializing in cloud-native Python microservices
Senior AI/ML Engineer specializing in Generative AI, LLMs, and data platforms
Mid-Level Full-Stack Software Engineer specializing in Java/Spring and AWS serverless
Mid-level Machine Learning Engineer specializing in Generative AI and LLMOps
Senior Supply Chain & Procurement Professional specializing in sourcing, inventory, and analytics
Senior Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Generative AI Engineer specializing in LLMs, RAG, and NLP systems
Akash Mishra
Mid-level Data Engineer specializing in ETL pipelines on GCP
“Full-stack engineer from Larix Technologies who led a Next.js migration feature: an internal real-time workflow status dashboard built with App Router/TypeScript using server components for initial render and client polling for live updates. Demonstrates strong post-launch ownership—monitoring latency/error rates, adding caching and payload reductions, and optimizing Postgres queries/indexes—plus experience building durable RabbitMQ-based message routing workflows with idempotency, retries, and dead-letter queues.”