AI, data engineering and payments automation for financial services
DataNimbus builds AI and data solutions for financial services and enterprise workflows, spanning payments orchestration and escrow automation. Its stack pairs a Java/Spring Boot and Kafka integration core with a deep ML layer (Databricks, Spark, MLflow, PyTorch, LangChain, OpenAI), and job posts point to client-facing delivery work: migrating legacy data to Databricks and putting LLMs on enterprise knowledge repositories. Hiring is minimal, senior-only and India-based.
DataNimbus is a privately held company founded in 2018 and headquartered in the Dallas - Fort Worth area of Texas, with 51–200 employees. It serves financial services firms and enterprises, focusing on AI-driven decisioning, intelligent automation, data integration and payments capabilities such as composable payments and escrow automation. Engineering runs across AWS, Azure and GCP with Docker and Kubernetes, backed by Java, Python and Scala services. Current hiring is limited to senior data and engineering roles in India.
DataNimbus uses Java, Spring Boot, Kafka, RabbitMQ, Docker and Kubernetes on AWS, Azure and GCP, plus Databricks, Apache Spark, MLflow, TensorFlow, PyTorch, Hugging Face, LangChain and OpenAI for data and AI work.
Yes. Databricks sits alongside Apache Spark, Scala and MLflow in its stack, and job posts mention migrating legacy data to Databricks and productionizing ML workloads.
DataNimbus is headquartered in the Dallas - Fort Worth area of Texas, United States, and its current senior data and engineering hiring is based in India.
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DataNimbus's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
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