Teams at Enable Data Incorporated

Designs Databricks data ingestion pipelines using PySpark and PySQL, develops and deploys Databricks Apps, and configures permissions, tokens, and service principals. Builds AI applications with FastAPI, React, Claude APIs, prompt engineering, vision processing, retrieval augmented generation, guardrails, graph analysis, and caching. Performs scenario-based testing, translates user requirements into code changes, and integrates custom notifications through APIs and webhooks.

Build and deploy production-ready AI applications and data pipelines on Azure Databricks. Responsibilities include PySpark and SQL ETL/ELT, CI/CD, Azure integrations, ML and generative AI deployment, RAG and vector search, LLM fine-tuning, monitoring, optimization, governance, and responsible AI. The role also involves Databricks Apps, Unity Catalog, prompt engineering, FastAPI and React applications, testing, guardrails, and collaboration with data science and platform teams.

Build Databricks data ingestion pipelines and AI applications using PySpark, FastAPI, React, Claude APIs, RAG, and Databricks services. Design cloud and network architectures, configure Azure resources, develop full-stack solutions, and automate deployments through Azure DevOps CI/CD. Implement testing, security remediation, validation scans, prompt engineering, AI guardrails, caching, and documentation while collaborating with technical and client stakeholders in short sprint cycles.