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Data Bricks Engineer at EXL Talent Acquisition Team

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

10 Sep, 26

Salary

0.0

Posted On

12 Jun, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, Delta Lake, Unity Catalog, Model Context Protocol, Python, TypeScript, Node.js, SSE, WebSockets, JSON-RPC 2.0, Databricks SQL, Managed MLflow, LLM Orchestration, Data Governance, Data Pipelines

Industry

Business Consulting and Services

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 and maintain secure connectors and pipelines between Databricks workspaces and Model Context Protocol (MCP) servers. Optimize data retrieval and ensure strict enterprise data governance for LLM applications.