SUMMARY

Yelp engineering culture is driven by our values: we’re a cooperative team that values individual authenticity and encourages creative solutions to problems. All new engineers deploy working code their first week, and we strive to broaden individual impact with support from managers, mentors, and teams. At the end of the day, we’re all about helping our users, growing as engineers, and having fun in a collaborative environment.
Yelp is seeking an entry-level Software Engineer who is excited to work at the intersection of data and backend engineering. In this role, you’ll help design and develop systems that power Yelp’s advertising platform—from building SDKs for large-scale event ingestion to designing data pipelines that process and analyze those events.
You’ll be joining the Product Monetization Platform team, which is responsible for collecting and processing ad-related events. Our work supports critical business functions, including billing, analytics, machine learning, and ad serving. This is a great opportunity to gain hands-on experience with scalable data systems while contributing to Yelp’s revenue-driving products.
This opportunity requires you to be located in the United Kingdom. We’d love to have you apply, even if you don’t feel you meet every single requirement in this posting. At Yelp, we’re looking for great people, not just those who simply check off all the boxes.

• Contribute to the experimentation and development of new ad products at Yelp.
• Design, build, and maintain efficient data pipelines using large-scale processing tools like Apache Spark to transform ad-related data.
• Manage high-volume, real-time data streams using Apache Kafka and process them with frameworks like Apache Flink.
• Estimate timelines for projects, feature enhancements, and bug fixes.
• Work with large-scale data storage solutions, including Apache Cassandra and various data lake systems.
• Collaborate with cross-functional teams, including engineers, product managers and data scientists, to understand business requirements and translate them into effective system designs.
• Support on-call rotations as needed to operate the team.