About the Team

The Data Control team provides the core compute and orchestration platform to power the current and next generation of data driven products at DoorDash. The team focuses on automation, reliability, and scalability while simplifying the experience for their end-users through curated abstractions. It aims to provide APIs for managing data infrastructure resources, ensuring vendor neutrality and automating common infrastructure management functions. Operationally, it serves as a single point of contact for vendors and focuses on capacity planning, cost optimization, and outage management.

About the Role

As a member of the Data Control team you’ll partner closely with Data Engineering, Analytics, ML Platform in addition to product engineering teams to provide a best in class data platform. This role needs to focus on maintaining flexibility while providing a guided, self-service experience that scales efficiently with the ever growing data volume and user demand.

You must be located in San Francisco, Sunnyvale, Seattle or New York City for this hybrid position. You will report into the Engineering Manager on our Data Control team.

You’re excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases.  You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We’re excited about you because… B.S., M.S., or PhD. in Computer Science or equivalent.6+ years of industry experience. Prior experience in Systems Engineering - you've built meaningful big data processing systems at scale, and have experience with big data compute engines such as Apache Spark and Apache Flink. Familiarity with distributed query engines Presto/Trino, Spark SQL or distributed OLAP stores Apache Pinot, ClickHouse or Star Rocks. Familiarity with orchestration frameworks such as Airflow or Dagster Familiarity with Data Lakes and table formats such as Delta Lake, Apache Iceberg. Familiarity with a cloud based environment such as AWS and managing services on Kubernetes. Professional experience with at least one of the programming languages such as Java, Scala Python or Go. Good knowledge of SQL. You are located or willing to relocate to the Bay Area, Seattle or NYC.

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