Data Bricks Engineer

• *Job Description: Role: Data Bricks Infra Engineer**

• *Location:** Gurgaon (5 days mandatory work from office)

• *Type:** Full\-time

• *Experience:** 8\+ years

• *Key Responsibilities**

• Design, build, and maintain secure connectors and pipelines between Databricks workspaces (Delta Lake, Unity Catalog) and Model Context Protocol (MCP) servers.
• Implement and configure MCP servers/clients to expose Databricks data, schemas, and analytical tools securely to AI models and LLM applications.
• Optimize data retrieval, caching mechanisms, and query performance between Databricks and LLM orchestration frameworks to minimize latency.
• Ensure all data exposed through the MCP server adheres to strict enterprise data governance, access controls, and Unity Catalog permissions.
• Partner with AI/ML engineers, data scientists, and software architects to define the context, tools, and prompts required for LLM applications to effectively query Databricks.

Establish robust logging, error\-handling, and monitoring for the Databricks\-MCP middleware to ensure high availability and reliability.

• *Must\-Have Skills**

• Proven, hands\-on experience building, configuring, or extending MCP servers (using Python or TypeScript/Node.js SDKs) to connect LLMs to external data sources.
• Deep production experience with Databricks (Delta Lake, Unity Catalog, Databricks SQL, and Managed MLflow
• Strong understanding of SSE (Server\-Sent Events), WebSockets, and JSON\-RPC 2\.0 protocols, which underpin MCP communication

• Responsibilities: Design, build, and maintain secure connectors and pipelines between Databricks workspaces (Delta Lake, Unity Catalog) and Model Context Protocol (MCP) servers.
• Implement and configure MCP servers/clients to expose Databricks data, schemas, and analytical tools securely to AI models and LLM applications.
• Optimize data retrieval, caching mechanisms, and query performance between Databricks and LLM orchestration frameworks to minimize latency.
• Ensure all data exposed through the MCP server adheres to strict enterprise data governance, access controls, and Unity Catalog permissions.
• Partner with AI/ML engineers, data scientists, and software architects to define the context, tools, and prompts required for LLM applications to effectively query Databricks.
• Establish robust logging, error\-handling, and monitoring for the Databricks\-MCP middleware to ensure high availability and reliability.

• Qualifications: Proven, hands\-on experience building, configuring, or extending MCP servers (using Python or TypeScript/Node.js SDKs) to connect LLMs to external data sources.
• Deep production experience with Databricks (Delta Lake, Unity Catalog, Databricks SQL, and Managed MLflow
• Strong understanding of SSE (Server\-Sent Events), WebSockets, and JSON\-RPC 2\.0 protocols, which underpin MCP communication