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Vetted Azure Data Factory Professionals
Pre-screened and vetted.
Senior Software & Data Engineer specializing in cloud platforms and streaming data
Mid-level Full-Stack Developer specializing in FinTech and fraud detection
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
VP Data Engineer specializing in AI-driven analytics platforms for investment management
Senior Data Engineer specializing in cloud data platforms and real-time pipelines
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
David Kidwell
Senior AI/ML Data Scientist specializing in NLP, computer vision, and MLOps
“Applied LLMs and a graph-RAG architecture in Neo4j to automate an accounting firm's cross-checking of transactional books against tax regulations, indexing 1,000+ pages into a knowledge graph with vector search. Combines agentic LLM workflows with classical NER (Hugging Face/NLTK) and validates using expert-labeled held-out data plus precision/recall and measured accountant time savings after deployment.”
Mid-level Software Engineer specializing in cloud-native microservices and real-time data pipelines
Mid-Level Full-Stack Software Engineer specializing in microservices and cloud
Mid-level Machine Learning & Generative AI Engineer specializing in enterprise RAG and MLOps
Mid-level Full-Stack Java Developer specializing in microservices and cloud platforms
Mid-level Full-Stack Software Engineer specializing in cloud-native data platforms
Junior Data Scientist specializing in causal inference, NLP/LLMs, and forecasting
Mid-level AI/ML Engineer specializing in Generative AI, LLMs, and RAG for financial services
Mid-level Data Engineer specializing in cloud-native ETL and data warehousing
Mid-level AI/ML Engineer specializing in NLP, MLOps, and financial risk & fraud analytics
Senior Data Scientist specializing in LLMs, NLP, and anomaly detection
Senior AI/ML Engineer specializing in GenAI, MLOps, and healthcare analytics
Mid-level AI/ML Product & Solutions Specialist specializing in GenAI and MLOps
Adithya Rajendra
Junior Data Engineer specializing in Azure data platforms and GenAI analytics
“Data/ML practitioner with experience spanning medical imaging (retinal vessel analysis for hypertension/CVD risk prediction) and enterprise data engineering at Carl Zeiss. Built large-scale SAP data cleaning/validation pipelines (10M+ daily records, ~99% accuracy) and RAG-based semantic search with LangChain/vector DBs that cut manual querying by 82%, plus automation that reduced data onboarding from 8 hours to 12 minutes.”