GridGain
GridGain is a Unified Real-Time Data Platform created by the original developers of Apache Ignite. It provides enterprises with a simplified and highly optimized data architecture that supports extreme speed, massive scale, and high availability for their data ecosystems. GridGain combines stream processing, a distributed in-memory data grid, and colocated compute to deliver data processing and analytics with ultra-low latencies. It is designed to seamlessly integrate both streaming data in-motion and historical data at-rest, enabling complex analytical and transactional workloads. The platform supports deployment across on-premises, public cloud, hybrid-cloud, and multi-cloud environments. GridGain is widely used in industries such as financial services, telecommunication, transportation, and logistics for real-time risk management, smart decisioning, and high-performance online transactional processing (OLTP), among other use cases.
In-Memory Computing • In-Memory Data Grid • Apache Ignite • Stream Processing • High Performance Transaction Processing
Senior Software Engineer - Java, Cloud Technologies
December 8, 2024
GridGain
GridGain is a Unified Real-Time Data Platform created by the original developers of Apache Ignite. It provides enterprises with a simplified and highly optimized data architecture that supports extreme speed, massive scale, and high availability for their data ecosystems. GridGain combines stream processing, a distributed in-memory data grid, and colocated compute to deliver data processing and analytics with ultra-low latencies. It is designed to seamlessly integrate both streaming data in-motion and historical data at-rest, enabling complex analytical and transactional workloads. The platform supports deployment across on-premises, public cloud, hybrid-cloud, and multi-cloud environments. GridGain is widely used in industries such as financial services, telecommunication, transportation, and logistics for real-time risk management, smart decisioning, and high-performance online transactional processing (OLTP), among other use cases.
In-Memory Computing • In-Memory Data Grid • Apache Ignite • Stream Processing • High Performance Transaction Processing
📋 Description
• Develop a backend for management and monitoring tools for GridGain In-Memory Platform. • Interaction with both, distributed clusters and user interfaces, will be required. • Cover your code with tests.
🎯 Requirements
• Experience with concurrent programming • 3+ years of software development experience with a strong focus on application development using Java • Experience with web technologies: Spring Boot / Spring Security / Spring Web MVC / Jetty • Experience with basic frameworks for unit testing (JUnit/TestNG) • Experience with databases • English — upper-intermediate or higher • Previous experience building medium to large-scale, mission critical, highly available production systems • Expertise in integration and E2E testing • Experience with Apache Ignite / GridGain • Experience with Docker, Kubernetes and/or public Cloud (AWS, GCE, Azure, etc.) • Knowledge of internal architecture of any DB • Experience with building distributed systems and algorithms • Deep knowledge of concurrency in Java and Java Memory Model and/or of concurrency model in other programming systems
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