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Vetted Azure Data Factory Professionals
Pre-screened and vetted.
Mid-level Data Analyst specializing in BI, analytics, and data engineering
Mid-level Full-Stack .NET Engineer specializing in cloud, APIs, and data analytics
Junior Data & BI Analyst specializing in analytics engineering, NLP, and financial risk analytics
Mid-Level Software Engineer specializing in backend, cloud, and data pipelines
Junior Software Developer specializing in full-stack and data engineering
Senior Data Engineer specializing in Machine Learning and Healthcare Data Platforms
Mid-Level Full-Stack .NET Engineer specializing in cloud, APIs, and data analytics
Mid-level Data Analyst specializing in BI and healthcare insurance analytics
Mid-level Software QA Engineer specializing in web, API, and test automation
Abhijeet Gajjar
Mid-level Mobile Software Engineer specializing in iOS, React Native, and AI-enabled backends
“Backend engineer who built and scaled a FastAPI-based backend for an AI-driven maintenance system automating vendor sourcing/bidding/communication. Emphasizes async, message-driven architecture with strong observability and state-machine-driven workflows, plus robust webhook/idempotency patterns to prevent duplicate/out-of-order events from causing bad bids or state changes.”
Junior Data Analyst & Business Analyst specializing in BI, analytics, and process optimization
Junior Machine Learning Engineer specializing in healthcare and IT analytics
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
Mid-level Full-Stack AI Engineer specializing in web and generative AI solutions
Mid-level Software Engineer specializing in Generative AI and cloud-native microservices
Mid-level Software Engineer specializing in Python automation and GenAI on AWS
Mid-Level Full-Stack Software Engineer specializing in cloud microservices and Voice AI
Mahaboob Johny
Mid-level Data Analyst specializing in SQL/Python analytics, ETL pipelines, and BI dashboards
“Data/AI practitioner who built a production LLM-driven healthcare claims analytics and dashboarding system to reduce avoidable ER visits—processing 1.4M+ claims, flagging 19% as non-emergent, and projecting ~$2.8M in annual savings. Demonstrates strong real-world LLM reliability and performance engineering (grounding, numeric validation, caching, materialized views, quantization) plus orchestration experience with Airflow and Azure Data Factory.”
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.”