Data Platform Engineer — Build Scalable Analytics Core

DoorDash, Inc.; San Francisco, Sunnyvale, Seattle, New York (CA, CA, WA, NY); On-site; USD 131,000 - 192,000; Full time

Job summary

DoorDash is expanding its Core Data Platform to support scalable data workflows and real-time personalization. You will help shape the platform's roadmap, balancing reliability, cost, and performance while enabling business-critical insights.

Ideal candidates have strong software engineering roots, 2+ years in big data, and fluency with Kafka, Flink, Spark, and related tools. You may relocate to the Bay Area, Seattle, or New York for this role.

Qualifications

• B.S., M.S., or PhD. in Computer Science or equivalent.
• 2+ years of industry experience in software engineering
• Proficiency using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle
• Big data experience across streaming, batch, data lake OLAP for real-time analytics
• Familiar with open-source data infra tools like DataHub, Spark, Airflow, Kafka, Flink (bonus)
• You are located or willing to relocate to the Bay Area, Seattle, or New York.

Responsibilities

• Drive vision & strategy for building the frameworks charter to scale with a growing business.
• Scale the analytical platform to handle increasing data and use cases.
• Build and operate high-scale systems with emphasis on reliability, scalability and cost efficiency.
• Collaborate with stakeholders to deliver platform solutions.
• Foster a positive, supportive culture and uplevel others.

Skills

Software engineering

Big data

AI coding tools

Cloud platforms

Relocation

Education

B.S./M.S./PhD in Computer Science or equivalent

Tools

Apache Kafka

Flink

Spark

Cassandra

ClickHouse

Iceberg

DataHub

Airflow

Job description

DoorDash is expanding its Core Data Platform to support scalable data workflows and real-time personalization. You will help shape the platform's roadmap, balancing reliability, cost, and performance while enabling business-critical insights.

Ideal candidates have strong software engineering roots, 2+ years in big data, and fluency with Kafka, Flink, Spark, and related tools. You may relocate to the Bay Area, Seattle, or New York for this role.