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Vetted Databricks Professionals
Pre-screened and vetted.
Mid-level Data Engineer specializing in cloud ETL, big data, and analytics
Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and NLP
Senior Data Engineer specializing in real-time pipelines, cloud data platforms, and healthcare analytics
Senior Data Analyst & Data Scientist specializing in healthcare, epidemiology, and predictive modeling
Mid-level Data Scientist specializing in ML, NLP, and cloud deployment
Senior Data Engineer specializing in AWS cloud data platforms and streaming analytics
Mid-level Data Scientist / ML Engineer specializing in NLP, GenAI, and cloud ML deployment
Mid-level Data Engineer specializing in lakehouse architectures and cloud ELT
Mid-level Data Engineer specializing in cloud data platforms for Healthcare and Financial Services
Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Senior DevOps/SRE Engineer specializing in multi-cloud infrastructure and Kubernetes
Senior AI Python Engineer specializing in Generative AI and MLOps
Venkatesh Nagubandi
Mid-level Software Engineer specializing in ML, LLM apps, and cloud data systems
“Built a production SQL chatbot for access-log analytics that replaced manual custom report requests with natural-language querying, using LangGraph and a ChromaDB-backed RAG pipeline for grounded, consistent answers. Implemented a privacy-preserving design where the LLM never sees raw customer data (only query metadata) and has experience building multi-agent/tool-calling systems with LangGraph (DeepAgents), including solving sub-agent communication drift via self-reflection.”
Satwik Koppala
Mid-level Full-Stack Java Developer specializing in digital banking and cloud microservices
“Backend-leaning full-stack engineer in lending/financial services (Kotak Mahindra Bank Autos360; currently at Ally Financial) working on Spring Boot microservices with React dashboards. Has built reliability improvements for credit-bureau integrations (Experian) and created an internal monitoring/reporting platform that aggregates metrics/logs/ETL across services, cutting troubleshooting by ~40%.”
Ankita Mungalpara
Mid-level Data Scientist specializing in Generative AI and multimodal systems
“Recent J&J intern who built a conversational RAG agent and led a shift from a monolithic model to a modular RAG workflow, cutting response time from several days to under a second by tackling data fragmentation, context retention, and embedding/latency optimization. Also worked on a large (7B-parameter) multimodal VQA pipeline for healthcare research and stays current via NeurIPS/ICLR and open-source contributions.”
Likith Kumar Tarala
Mid-level Machine Learning Engineer specializing in deep learning and generative AI
“AI/ML engineer who has deployed transformer-based NLP systems to production via Python REST APIs and Kubernetes on AWS/Azure, with a strong focus on latency optimization (p95), reliability, and scalable orchestration. Demonstrates pragmatic model tradeoff decision-making and strong stakeholder collaboration—improving adoption by making outputs more actionable with summaries, extracted fields, and confidence indicators.”
Erik Moyer
Director-level Data Science & Analytics Leader specializing in cloud data platforms and AI/ML
“Candidate states they are very familiar with the venture capital/studio/accelerator landscape and expresses strong willingness to pursue entrepreneurship "at all costs," but did not provide details on a current startup, business plan, fundraising, or prior accelerator/VC involvement during the interview.”