Software Engineer, Data Platform (Go/Kafka)

About the role

Cato Networks is looking for an experienced Software Engineer to join its Data Platform Group. You will build the company's cloud-based microservices and data pipelines that process about 1 million records per second at low latency. The Streaming team owns the real-time heart of the platform, ingesting, enriching, aggregating and routing data in motion, and delivering it to customers through external integrations.

Key responsibilities

• Take end-to-end ownership of the real-time stream processing layer: ingestion, enrichment, aggregation and routing of high-volume data at low latency.
• Design and develop high-performance stream processing services in Go, built on Kafka/MSK.
• Build and evolve stateful stream processing pipelines, including Kafka Streams-based applications.
• Partner with Product to define, design and implement external connectors that export data to customers' systems.
• Own performance and resource efficiency: profile and optimize hot paths, reduce memory footprint and allocations, and lower compute costs at scale.
• Design for reliability under load, including backpressure, partitioning, consumer-group strategies, ordering, delivery guarantees and idempotency.
• Research new stream processing technologies and adapt them for use in the product.
• Work closely with Product, DevOps, Security and the other teams in the Data Platform Group.

Required profile

• 5+ years of hands-on experience designing and developing high-throughput, low-latency distributed systems in production.
• B.Sc. in Computer Science, Software Engineering or a related field, or equivalent practical experience.
• A motivated, independent learner and strong problem solver, with excellent collaboration and communication skills.

Required skills

• Deep hands-on experience with Kafka at significant scale: partitioning, consumer groups, offset management, producer/consumer tuning and throughput vs. latency trade-offs.
• Experience building and running microservices on Kubernetes, including resource tuning and autoscaling.
• Hands-on experience with AWS, particularly MSK, EKS and EC2.
• Familiarity with Go and Java fundamentals is a major advantage.
• Basic hands-on experience with AI coding assistants or development tools, with the ability to review and validate generated code.