Senior Software Engineer, Backend (Streaming Infrastructure)
Software Development
WFA Digital Insight
As the demand for real-time data processing grows, companies like Affirm are seeking experts to lead their streaming infrastructure. With a 25% increase in remote tech jobs in 2025, this role stands out for its focus on event-driven architecture and scalable data pipelines. Candidates should be prepared to showcase their expertise in stream processing technologies and passion for building fault-tolerant systems.
Job Description
About the Role
The Streaming team at Affirm forms the backbone of several online and offline workloads, driving the strategy for event-driven architecture, stream processing, replication, data exploration, discovery, and validation. We leverage existing open-source technologies like Kafka, Flink, and Spark to design and build real-time data processing pipelines.Responsibilities
- Own and deliver quarterly goals for your team
- Lead engineers through ambiguity to solve open-ended problems
- Collaborate with product management, design, and analytics to promote optimal use of data
- Proactively identify project, process, technology, or business issues and lead in solving them
- Foster a culture of quality and ownership on your team
Requirements
- 4+ years of experience designing, developing, and deploying scalable data infrastructure
- Deep expertise in stream processing technologies
- Passion for building fault-tolerant data infrastructure
How to Stand Out
- Develop a strong understanding of Kafka, Flink, and Spark, and be prepared to discuss their applications in real-time data processing
- Showcase your experience with event-driven architecture and scalable data pipelines in your portfolio or during interviews
- Highlight your ability to collaborate with cross-functional teams, including product management and design
- Be prepared to discuss your approach to identifying and solving complex technical issues
- Emphasize your passion for building fault-tolerant systems and your experience with stream processing technologies
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