Software Engineer - Batch Compute

The Batch Compute team at Stripe manages the infrastructure, tooling and systems behind running batch processing systems at Stripe, which are currently powered by Hadoop and Spark. Batch processing systems power several core asynchronous workflows at Stripe and operate at significant scale. 

What you’ll do

• We're looking for a Software Engineer with experience designing, building and maintaining high-scale, distributed systems.
• You will work with a team that is in charge of the core infrastructure used by the product teams to build and operate batch processing jobs.
• You will have an opportunity to play a hands-on role in significantly advancing our current infrastructure to be much more efficient and resilient. 

Responsibilities

• Scope and lead technical projects within the Batch Compute domain
• Build and maintain the infrastructure which powers the core of Stripe.
• Directly contribute to core systems and write code.
• Work closely with the open source community to identify opportunities for adopting new open source features as well contribute back to the OSS.
• Ensure operational excellence and enable a highly available, reliable and secure Batch Compute platform

Who you are

We’re looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are encouraged to apply. The preferred qualifications are a bonus, not a requirement.

Minimum requirements

• 5+ years of professional experience writing high quality production level code or software programs.
• Have experience with distributed data systems such as Spark, Flink, Trino, Kafka ,etc
• Experience developing, maintaining and debugging distributed systems built with open source tools.
• Experience building and scaling infrastructure as a product

Preferred qualifications

• Experience as a user of batch processing, authoring and optimizing Spark applications
• Experience building and maintaining data pipelines
• Open source contributions to data processing or big data systems (Hadoop, Spark, Celeborn, Flink, etc)