Software Engineer Data Platform (Go/Kafka)

Location: Tel Aviv District, Israel

Company

hirify.global provides a unified, cloud-native network and security platform with visibility and real-time threat protection across users, applications, data, and AI agents.

What you will do

• Own the real-time stream processing layer for ingestion, enrichment, aggregation, and routing of high-volume data at low latency.
• Design and develop high-performance Go services and Kafka/MSK-based pipelines.
• Build and evolve stateful stream-processing applications and external connectors that deliver data to customer systems.
• Profile hot paths, optimize CPU utilization, reduce memory footprint and allocations, and lower compute costs at scale.
• Design for reliability under load, including backpressure, partitioning, consumer groups, ordering, delivery guarantees, and idempotency.
• Research stream-processing technologies and collaborate with Product, DevOps, Security, and Data Platform teams.

Requirements

• 5+ years of hands-on experience designing and developing high-throughput, low-latency distributed systems in production.
• Deep, hands-on Kafka experience at significant scale, including partitioning, consumer groups, offset management, producer/consumer tuning, and throughput-versus-latency trade-offs.
• Familiarity with Go and Java fundamentals is a major advantage.
• At least basic hands-on experience with AI coding assistants or development tools for implementation, testing, and debugging, including reviewing and validating generated code.
• Experience building and running microservices on Kubernetes, including resource requests and limits tuning and autoscaling configuration.
• Hands-on AWS experience, particularly with MSK, EKS, and EC2.
• Motivated, independent learning ability and strong problem-solving skills.
• Strong collaboration and communication skills.
• B.Sc. in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Culture & Benefits

• Work on a cloud-native data platform supporting engineering, product, research, and customer-facing systems.
• Collaborate across Product, DevOps, Security, and Data Platform teams.
• Operate at approximately 1M records per second, where CPU efficiency, memory footprint, and correctness are core engineering concerns.