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Vetted dbt Professionals
Pre-screened and vetted.
Senior Data Engineer specializing in real-time platforms and GenAI analytics
Director-level Engineering Leader specializing in Healthcare AI and data platforms
Senior Business Analyst specializing in analytics engineering and FinTech data solutions
Mid-level Data Engineer specializing in real-time streaming and AI/ML data platforms
Executive technology leader specializing in AI-native platforms and data infrastructure
Director-level AI and data science leader specializing in clinical data and analytics
Mid-level Data Analyst specializing in financial and healthcare analytics
Senior Data Scientist specializing in GenAI, MLOps, and cloud data platforms
Mid-level Machine Learning Engineer specializing in MLOps and LLM/RAG systems
Senior Data Engineer specializing in cloud lakehouse platforms for banking and healthcare
Mid-Level Data Engineer specializing in cloud data pipelines and lakehouse/warehouse platforms
Mid-level Software Engineer specializing in AI and cloud data platforms
Mid-level Data Engineer specializing in cloud data pipelines and analytics (AWS/Azure)
Mid-level Data Engineer specializing in big data pipelines and cloud data platforms
Mid-level Business Analyst specializing in healthcare analytics and interoperability
Senior Data Scientist specializing in ML engineering and cloud analytics
Bharath Reddy Nallu
Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps
“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”
Likitha Kukunarapu
Mid-level Applied AI Engineer specializing in data engineering and healthcare AI
“Built production LLM agents spanning document Q&A, financial insight generation, and ERP-like operational data workflows, with a strong focus on reliability, grounding, and evaluation. Stands out for translating LLM systems into measurable business outcomes, including 70%–80% support workload reduction and a fallback-rate improvement from 18% to 8% through targeted RAG iteration.”
Soumya Nayak
Mid-level Software Engineer specializing in cloud-native systems and AI automation
“Software engineer with hands-on experience shipping production AI agents and end-to-end ecommerce workflows. They built a customer support automation agent with strong guardrails and evaluation practices, then improved it post-launch using real user data to cut latency ~30% and token cost ~25%. Also drove a zero-to-one self-serve order modification product across React UI, backend services, and cross-functional alignment.”