Backend Engineer

About The Position

Coralogix is a modern, full-stack observability platform transforming how businesses process and understand their data. Our unique architecture powers in-stream analytics without reliance on expensive indexing or hot storage. We specialize in comprehensive monitoring of logs, metrics, traces and security events with features such as APM, RUM, SIEM, Kubernetes monitoring and more, all enhancing operational efficiency and reducing observability budget by up to 70%.

About The Role

We are looking for a Backend / Data Engineer to join our Core Data Pipeline team. In this role, you will be responsible for building and scaling the engine that processes Coralogix’s high-throughput, real-time telemetry data.

Our pipeline handles billions of events per second, performing real-time processing, data enrichment, and other transformations. If you thrive on solving high-scale, low-latency distributed systems challenges - this is the place for you.

What You’ll Do

• High-Scale Engineering: Design, build, and maintain our central data processing pipeline, handling massive volumes of logs and traces at extreme scale.
• Transform & Enrich: Architect real-time stream processing systems to perform complex data transformations and enrichments in real time.
• Performance & Efficiency: Optimize system throughput, reduce memory footprints, and minimize latency across distributed clusters.
• Architecture & Reliability: Take full ownership of feature lifecycles - from design and system architecture to production monitoring and resilience.
  
  

• Scala, Rust, Node.js
• Kafka
• Kafka Streams / Akka Streams
• ClickHouse, Redis
• Kubernetes
• AWS
  
  

• 4+ years of development experience with Scala or another JVM language.
• Extensive hands-on experience with scalable and distributed systems architecture and design.
• Extensive hands-on experience with Data Streaming technologies, including Apache Kafka, Spark Streaming, KafkaStreams, or Apache Flink.
• Proficiency in data modeling and designing systems to handle large-scale, distributed datasets efficiently.
• Experience with containerization and orchestration tools, including Kubernetes and Docker containers.
• Strong knowledge of distributed computing paradigms and principles, such as consistency, partitioning, and resilience.
• B.Sc. in Computer Science or an equivalent field.
  
  

• Production experience in a SaaS environment - Metrics, Logging, Troubleshooting production systems
• API development experience with gRPC