below marketmost similar roles pay hereabove market
This role pays more than
54%
of similar roles. Most pay
$146,650–$202,800
— the blue band above.
At the midpoint, this role pays about
$161k
versus about
$175k
for comparable roles.
Based on 240 similar postings.
Employer
About DoorDash, Inc
DoorDash, Inc. is an American company operating online food ordering and food delivery. It trades under the symbol DASH. With a 56% market share, DoorDash is the largest food delivery platform in the United States.
DoorDash, Inc currently has
97 open roles
on FindRole.
Listed pay typically runs
$163,800–$240,900
across 96 roles with salary data.
The Software Engineer, Data Platform joins the Core Data Platform organization to own the infrastructure necessary for an operationally efficient analytical data stack. This role involves designing and operating scalable compute and ingestion frameworks while building abstractions and tools to simplify workflows for engineers, analysts, and ML practitioners. You will drive the vision for the frameworks charter, focusing on reliability, scalability, and cost efficiency to handle a rapidly growing business. Key responsibilities include establishing data quality, cataloging, privacy, and compliance standards. You will utilize technologies including Spark, Flink, Kafka, Airflow, Cassandra, Clickhouse, and Iceberg. The role requires expertise in big data domains such as streaming, batch, and data lake OLAP to enable business-critical insights and real-time personalization capabilities while improving overall platform stability.
What does a Software Engineer earn in California?
Median $214500 from 1193 postings across 76 companies.
Drive the vision and strategy for building the frameworks charter to handle business growth.
Scale the analytical platform to support increasing amounts of data and diverse use cases.
Build and operate high-scale systems with a focus on reliability, scalability, and cost efficiency.
Design and operate scalable compute and ingestion frameworks using Spark, Flink, Kafka, and Airflow.
Build abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners.
Establish data quality, cataloging, privacy, and compliance standards to ensure trust in analytics.
Improve the efficiency, scalability, and stability of the core data platform.
What we're looking for
Must hold a B.S., M.S., or PhD. in Computer Science or an equivalent degree.
Must have 2+ years of industry experience in software engineering.
Must be located in or willing to relocate to San Francisco, Sunnyvale, Seattle, or New York.
Must be proficient in using AI coding tools throughout the full software development lifecycle.
Must have experience in big data domains including streaming, batch, and data lake OLAP using technologies like Kafka, Flink, Spark, Cassandra, or Clickhouse.
Must have technical experience building and operating big data infrastructure and governance.
Must have experience improving the efficiency, scalability, and stability of data platforms.
Prior experience with open-sourced technologies like DataHub, Spark, Airflow, Kafka, or Flink is a bonus (preferred).