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# Software Engineer, Data Platform (All Levels, All Teams)

- **Company:** DOORDASH, INC.
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Apache HTTP Server, Big Data, Data Discovery, Data Governance, Data Infrastructure, Data Systems, Python (Programming Language), Online Analytical Processing, Open Source Technology, Scala (Programming Language), Data Processing, Apache Spark, Information Technology, Apache Flink, Apache Kafka, Data Management, Stream Processing, Programming Languages
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_37f688099b93e5bd6952b1e5c84e53fc

## About the Role

* S., M.S., or PhD. in Computer Science or equivalent
 * 2+ years of experience with CS fundamental concepts and experience with at least one of the programming languages of Scala, Java, and Python
 * You are located or are willing to locate to the Bay Area or Seattle
 * Prior technical experience in Big Data infrastructure & governance - you've built meaningful pieces of data infrastructure. Bonus if those were open-source technologies like DataHub, Spark, Airflow, Kafka, Flink
 * Experience improving efficiency, scalability, and stability of data platforms

## Description

The Data Governance Platform team's mission is to build robust data platforms and establish policies that guarantee the analytics data is of high quality, easily accessible/cataloged, and compliant with financial and privacy regulations, fostering trust and confidence in our data-driven decision-making process. The team is relatively small, so there's an opportunity for impact where you can help grow the team and shape the roadmap for the data platform at DoorDash. You will report directly to the Data Governance Platform Engineering Manager. You must be located in the Bay Area or Seattle for this hybrid role.

The Realtime Platform powers business starting from realtime data collection, to data processing which enables Data Scientists and ML Engineers for analytics, to out-of-box realtime feature and signal generation providing customers a personalized experience. The platform provides a complete solution including infrastructure and framework using open-source technologies such as Apache Kafka, Apache Flink, Apache Spark. The solution also offers realtime insights as a product integrated with in-house services and OLAP such as Apache Pinot. The team consists of a mix of experienced veterans of stream processing from prestigious companies and some inspiring and passionate budding streaming engineers.

The Unified Metrics Platform Team is a relatively new team that has taken on the charter of building a single source-of-truth internal platform for all business metrics at DoorDash. This platform aims to unify multiple existing metrics systems which together offer a complex mix of overlapping and disparate features into a consistent offering that provides all necessary features that our customers need in a simple and intuitive manner. The goals of the platform are to standardize metric definitions, standardize access to metrics data for consumption as well as standardize metric computations across the full spectrum of batch to near realtime. Our customer personas include C-suite executives, business leaders and decision makers, product owners, analysts, data scientists, product engineers, data engineers, ML engineers, marketers, operators and many others. Their use cases span across experimentation, dashboarding, alerting and reporting among many others., * Work on building a data discovery platform, privacy frameworks, unified access control frameworks, and data quality platform to enable data builders at DoorDash to deliver high-quality and trustable data sets and metrics

 * Help accelerate the adoption of the data discovery platform by building integrations across online, analytics platforms and promoting self-serve
 * Come up with solutions for scaling data systems for various business needs
 * Collaborate in a dynamic startup environment