Data Platform Engineer – AI-Driven Analytics

DoorDash; San Francisco, Sunnyvale (CA, CA); On-site; USD 131,000 - 285,000; Full time

Benefits offered by this job

Equity grants

401(k) plan

Paid parental leave

Wellness benefits

Commuter benefits

Paid time off

Job summary

DoorDash is building a world-class data platform team to own the full path from a question to an answer, powering dashboards, reports, and AI-assisted analytics for thousands of users across our marketplace. You will collaborate with data engineers, product teams, and operators to shape the semantic layer, governance, and multicore caching as you deliver reliable insights in production.

You will partner on semantic modeling, data discovery, and metadata workflows while evolving the AI

Qualifications

• B.S., M.S., or PhD. in Computer Science or equivalent.
• 3+ years of industry experience in software engineering.
• Strong backend fundamentals, especially in Go, Python and the ability to own a service in production.
• Shipped an LLM-powered feature to real users, hands-on with retrieval and grounding and built or meaningfully extended an eval system.
• Built meaningful pieces of data platform products- semantic layers, data discovery, reporting applications, caching systems and data applications.
• Familiarity with a cloud-based environment such as AWS and with Kubernetes in production.
• Experience with MCP, agent frameworks, or tool-calling architectures in production.
• Experience with traditional and modern reporting or analytics tooling, data governance, controls and multi-tenant data platforms.
• Prompt and context optimization at scale - caching, token budgeting, cost/latency tuning.

Responsibilities

• Ship agentic analytics features to thousands of users where a wrong number is a real business decision made badly, and accuracy is the product.
• Build a data platform for authoring, dashboard runtime, drill-down and cross-filter semantics, scheduling and alerting, content certification and permissions, and the embedding path that puts the same components in front of external users.
• Build the AI experience inside that platform: agent-assisted query authoring, generated charts and widgets held to the same governance as hand-built ones.
• Evolve the semantic layer metric and dimension modeling, definition governance, lineage and expose metadata in forms a model can actually reason over.
• Own the query and adaptive caching path: planning and federation across different query engines and invalidation correctness, and safe execution under agent traffic that bursts and fans out.
• Develop AI-enabled services and workflows, including self-serve tooling for creating, evaluating, and improving AI assistants.
• Build and operate data discovery and metadata platforms that help users find the right datasets, dashboards, and metrics quickly and confidently.

Skills

Go

Python

LLM features

Retrieval grounding

AWS

Kubernetes

MCP

Tool-calling

Data governance

Caching systems

Prompt optimization

Full stack

Education

Bachelor's/Master's/PhD in CS

Tools

Snowflake

Spark

ClickHouse

Kubernetes

Job description

DoorDash is building a world-class data platform team to own the full path from a question to an answer, powering dashboards, reports, and AI-assisted analytics for thousands of users across our marketplace. You will collaborate with data engineers, product teams, and operators to shape the semantic layer, governance, and multicore caching as you deliver reliable insights in production.

You will partner on semantic modeling, data discovery, and metadata workflows while evolving the AI