.png){kind=logo}
Vetted Data Modeling Professionals
Pre-screened and vetted.
Intern Data Engineer specializing in cloud data pipelines and network security research
Senior Backend Engineer specializing in Kubernetes, GitOps, and Kafka streaming
Junior Software Engineer specializing in distributed systems and AI
Mid-level Software Engineer specializing in cloud-native microservices and FinTech
Mid-level Full-Stack Software Engineer specializing in Spring Boot microservices and React
Mid-level Data Engineer specializing in cloud ETL, big data, and analytics
Mid-level Full-Stack Software Engineer specializing in cloud-native microservices
Senior Data Engineer specializing in real-time pipelines, cloud data platforms, and healthcare analytics
Senior Software Development Engineer specializing in full-stack web, cloud, and MLOps
Senior Data Engineer specializing in AWS cloud data platforms and streaming analytics
Mid-level Data Analyst specializing in BI dashboards, SQL optimization, and cloud data pipelines
Senior Full-Stack Software Engineer specializing in React, React Native, and Spring Boot
Junior Online/Full-Stack Developer specializing in live-service game backend systems
Mid-level Data Engineer specializing in cloud data platforms for Healthcare and Financial Services
Senior AI Python Engineer specializing in Generative AI and MLOps
Banchode Hari
Mid-level Full-Stack Developer specializing in microservices and event-driven systems
“Full-stack engineer with end-to-end ownership of a production customer plan activation and account management flow at T-Mobile, spanning Java/Spring Boot APIs, React frontend, and Docker-based CI/CD deployments. Demonstrated performance/scalability work (query optimization, indexing, caching) and measured success via improved retrieval speed and reduced support tickets.”
Pravallika Kilari
Mid-level AI/ML Engineer specializing in NLP, GenAI, and MLOps in healthcare and finance
“AI/ML engineer with CVS Health experience deploying production LLM systems in regulated healthcare settings, including a large-scale RAG solution (1M+ documents) built for compliance-grade, auditable policy/regulatory Q&A with strong anti-hallucination controls. Also delivered an NLP summarization system for physician notes/case narratives by partnering closely with non-technical care operations stakeholders and iterating via prototypes, dashboards, and feedback loops.”
Chandan Chalumuri
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
“Data engineering / ML practitioner with experience at MetLife building transformer-based sentiment analysis over large unstructured datasets and productionizing pipelines with Airflow/PySpark/Hadoop (reported 52% efficiency gain). Also implemented embedding-based semantic search using Pinecone/Weaviate to improve retrieval relevance and enable RAG for customer support and document matching use cases.”