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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and maintaining secure data pipelines and connectors between Databricks and MCP servers, with a strong focus on data governance and performance optimization. Proficient in collaborating with AI/ML engineers and data scientists to enhance LLM applications through effective data exposure and query mechanisms.
Highest-signal resume keywords
Databricks ExperienceMCP Server ConfigurationData GovernancePython ProgrammingTypeScript/Node.js SDK
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringDelta LakeUnity CatalogDatabricks SQLManaged MLflowSSE ProtocolWebSocketsJSON-RPC 2.0Data OptimizationQuery Performance
Tools & Technologies
DatabricksMCP ServersAI ModelsLLM Applications
Industry Keywords
Data GovernanceAccess ControlsEnterprise DataMiddlewareError Handling
Tech Stack
Tools & technologiesJavaScriptNode.jsPythonSQLTypeScriptUnity
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- Graduate in Computer Science, Data Science, or related field
- 8+ years of experience in data engineering or a related field.
- 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
Benefits
Comp & perks- Health insurance
- Retirement plans
- Paid time off
- Flexible work arrangements
- Professional development
