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DoorDash is looking to solve the problem of providing a scalable and reliable abstraction layer for data engineers and machine learning engineers to accomplish their analytics workflows, and to build a cost-effective, AI-infused, self-serve analytics platform leveraging open source products strategically.

Requirements

• 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 Datalakes and table formats such as Delta Lake, Apache Iceberg.
• Familiarity with a cloud based environment such as AWS.
• Professional experience with at least one of the programming languages such as Java, Scala Python or Go. Good knowledge of SQL.
• Experience with declarative data transformations, data quality assertions, metric cube computation and spark connectors to ML feature stores.
• Experience with building and operating high scale systems with a focus on reliability, scalability and cost efficiency.
• Experience with AI and machine learning technologies.

Responsibilities

• Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing global business.
• Leverage AI to continuously improve team productivity. Make the products we build work well with AI tools.
• Bring 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, evangelizing and partnering with other teams effectively.
• Foster a positive and supportive work culture, upleveling others.
• Provide technical leadership to enable the vision of a cost effective, AI infused, self-serve analytics platform leveraging open source products strategically.
• Act as a force multiplier to deliver reliable solutions at scale.

Other

• B.S., M.S., or PhD. in Computer Science or equivalent.
• 8+ years of industry experience.
• 2+ years of experience at the staff level, providing technical leadership to the team.
• You are located or willing to relocate to the Bay Area or Seattle.
• Ability to work in a hybrid environment.