GridGain
SaaS • Finance • Telecommunications
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.
51 - 200 employees
☁️ SaaS
💸 Finance
📡 Telecommunications
Senior Software Engineer — С++
Job not on LinkedIn
July 28
GridGain
SaaS • Finance • Telecommunications
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.
51 - 200 employees
☁️ SaaS
💸 Finance
📡 Telecommunications
📋 Description
• Develop and optimize data structures for high data-intensive scenarios • Implement the best way to store data to disk and sending data via network to other nodes • Implement and integrate algorithms for high availability of the whole cluster • Investigate flaws in data consistency algorithms
🎯 Requirements
• Deep knowledge of concurrency in C++ • 5+ years experience in C++ programming • Experience with SQL databases • English — upper-intermediate or higher • Experience with NoSQL and/or distributed databases • Experience with building distributed systems and algorithms • Hands-on experience with GPU development (CUDA, OpenCL) • Understanding of query execution pipeline (query planning and execution) • Knowledge of Java and Java Memory Model • Experience with Docker, Kubernetes and/or public Cloud (AWS, GCE, Azure, etc.)
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