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Vetted Azure Data Factory Professionals
Pre-screened and vetted.
Executive Technology Architect & CTO specializing in cloud transformation and cybersecurity
Mid-level AI/ML Engineer specializing in fraud detection and customer lifetime value modeling
Mid-level Data Analytics Engineer specializing in cloud data platforms and FinTech
Mid-level Software Engineer specializing in backend microservices, data pipelines, and QA
Mid-level Business Data Analyst specializing in healthcare and financial analytics
Mid-level Data Scientist specializing in LLMs, RAG, and personalization
Mid-level Data Scientist specializing in ML, NLP, and fraud/anomaly detection
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Machine Learning Engineer specializing in NLP, federated learning, and fraud detection
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
Mid-level Data Engineer specializing in cloud lakehouse platforms (Azure/AWS/Snowflake)
Senior Data/GenAI Engineer specializing in cloud-native ML, RAG, and real-time data platforms
Mid-level Business Analyst specializing in data analytics and enterprise reporting
Senior Software Engineer specializing in data engineering, BI analytics, and AI/ML
Sharath Nyalakonda
Mid-level AI/ML Engineer specializing in NLP, graph models, and MLOps for FinTech and Healthcare
“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”
Justin Turner
Executive Technology Leader (CTO/CIO/CISO) specializing in cloud, security, and data platforms
“CTO-level technology leader with experience building end-to-end tech strategy and roadmaps, modernizing legacy environments in healthcare (GenesisCare), and scaling engineering into large global teams (Amadeus). Built a DevOps organization at Syniverse for the Visibility Suite, implementing Kubernetes/Terraform/Chef automation that drove ~75% faster deployments, and is known for staying hands-on (including data center work) while leading strategically.”
Vikas Ravula
Senior Data Engineer specializing in cloud data platforms and real-time streaming for financial services
“Data engineer with experience at Bloomberg, UBS, and Bank of America building high-volume financial data platforms and services. Owned an end-to-end pipeline processing ~150–200M records/day (Kafka/Cassandra/S3 → Spark/PySpark → Snowflake) with strong data quality controls and Airflow reliability practices, reporting ~99% reliability and major performance gains. Also built large-scale external API ingestion with compliance-minded rate limiting, schema versioning, and quarantine/validation layers.”
Vasanthi Koya
Senior Full-Stack/Data Engineer specializing in cloud data pipelines for legal and financial platforms
“Data/analytics engineer who built and operated a DocuSign-based real-time analytics platform end-to-end, processing 20–50k webhook events/day with ~99.5% reliability. Strong in idempotent event processing, schema-evolution-safe ingestion (raw JSON + dynamic parsing), and serving data via versioned, low-latency REST APIs with solid CI/CD and observability.”
Kaustubh Rai
Junior Software Engineer specializing in scalable distributed systems and cloud platforms
“Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.”
Meghashree N
Mid-level AI/ML Engineer specializing in recommender systems, NLP, and cloud ML
“AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.”