Data & AI Platform Engineer — LLM-Driven Analytics

DoorDash, Inc.; Sunnyvale (CA); On-site; USD 131,000 - 192,000; Full time

Job summary

DoorDash, Inc. is seeking an experienced data platform engineer to own the end-to-end path from a user question to an actionable answer for dashboards and reports. You will work on BI surfaces, semantic layers, and AI-enabled analytics in production, serving a wide range of users across the organization.

You will collaborate with data scientists and engineers to design scalable query, caching, and governance strategies, shipping agentic analytics features and expanding data platform capabilities.

Qualifications

• B.S., M.S., or PhD in Computer Science or equivalent.
• 3+ years of industry experience in software engineering.
• Strong backend fundamentals, especially Go and Python, with production ownership.
• Shipped an LLM-powered feature with retrieval/ grounding and eval systems.
• Experience with MCP, data governance, and multi-tenant data platforms.

Responsibilities

• Own the full path from a question to an answer for BI reporting surfaces.
• Ship agentic analytics features and scale to thousands of users.
• Develop data platform components: semantic layer, caching, and orchestration.
• Collaborate across data engineering, analytics, and product teams to deliver end-to-end dashboards.

Skills

Go

Python

Production service ownership

LLM

AWS

Kubernetes

MCP

Agent frameworks

Data governance

Analytics tooling

Education

B.S., M.S., or PhD in Computer Science

Tools

Snowflake

Spark

ClickHouse

Job description

DoorDash, Inc. is seeking an experienced data platform engineer to own the end-to-end path from a user question to an actionable answer for dashboards and reports. You will work on BI surfaces, semantic layers, and AI-enabled analytics in production, serving a wide range of users across the organization.

You will collaborate with data scientists and engineers to design scalable query, caching, and governance strategies, shipping agentic analytics features and expanding data platform capabilities.