Data Platform Engineer: Scale Real-Time Analytics

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

Benefits offered by this job

401(k) matching

Parental leave

Wellness benefits

Commuter benefits match

Paid time off

Medical insurance

Dental insurance

Vision benefits

Holidays

Life insurance

Mental health program

Job summary

DoorDash’s Core Data Platform team seeks a senior data platform engineer to design and operate scalable data infra, enabling real-time personalization and trusted analytics. You will influence roadmaps, drive reliability, and champion governance across streaming, batch, and lakehouse workloads.

The role emphasizes collaboration across engineers, analysts, and ML teams, with opportunities to shape platform decisions and impact business insights.

Qualifications

• BS/MS/PhD in Computer Science or equivalent.
• 2+ years of industry experience in software engineering.
• Proficiency with AI coding tools across the full SDLC.
• Experience with big data domains and real-time analytics (Kafka, Flink, Spark, data lake tech).
• Experience building data infrastructure and governance; familiarity with open-source tools.

Responsibilities

• Drive vision and strategy for the frameworks charter to support a growing business.
• Scale the analytical platform for increasing data and use cases.
• Build and operate high-scale, reliable, and cost-efficient data systems.
• Collaborate with stakeholders to build solutions on top of the platform.
• Foster a positive, supportive culture and uplift teammates.

Skills

Software engineering

Big data

Reliability

Cost efficiency

AI coding tools

Education

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

Tools

Apache Kafka

Flink

Spark

Airflow

Cassandra

ClickHouse

Iceberg

DataHub

Job description

DoorDash’s Core Data Platform team seeks a senior data platform engineer to design and operate scalable data infra, enabling real-time personalization and trusted analytics. You will influence roadmaps, drive reliability, and champion governance across streaming, batch, and lakehouse workloads.

The role emphasizes collaboration across engineers, analysts, and ML teams, with opportunities to shape platform decisions and impact business insights.