Data Platform Engineer: Scale & Real-Time Analytics

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

Benefits offered by this job

401(k) matching

Paid parental leave

Health, dental, vision benefits

Paid time off

Job summary

DoorDash, a data-driven tech company, is seeking a Data Platform Engineer in the San Francisco Bay Area to design and operate scalable data infrastructure, spanning ingestion, compute and governance. You will work with Spark, Flink, Kafka, Airflow, and lakehouse tech to empower real-time insights and personalization.

You will join a team that emphasizes reliability, cost efficiency, and collaboration with engineers, analysts, and ML practitioners while shaping the platform roadmap and ensuring

Qualifications

• BS/MS/PhD in Computer Science or equivalent required.
• 2+ years of software engineering experience.
• Experience with large-scale data systems and ML workflows.

Responsibilities

• Design and operate scalable data platform components.
• Collaborate with engineers, analysts, and ML teams to deliver reliable data tooling.
• Drive data quality, cataloging, privacy, and governance standards.

Skills

AI coding tools

Big data platforms

Reliability & scalability

Collaboration with stakeholders

Cost efficiency

Education

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

Tools

Apache Kafka

Flink

Spark

Cassandra

ClickHouse

Iceberg

DataHub

Airflow

Job description

DoorDash, a data-driven tech company, is seeking a Data Platform Engineer in the San Francisco Bay Area to design and operate scalable data infrastructure, spanning ingestion, compute and governance. You will work with Spark, Flink, Kafka, Airflow, and lakehouse tech to empower real-time insights and personalization.

You will join a team that emphasizes reliability, cost efficiency, and collaboration with engineers, analysts, and ML practitioners while shaping the platform roadmap and ensuring