GridGain
SaaS âą Finance âą 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.
Senior Software Engineer - Java
Job not on LinkedIn
December 11, 2024
GridGain
SaaS âą Finance âą 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.
đ Description
âą Develop and optimize data structures for best experience accessing data in high data-intensive scenarios âą Implement the best way to store data to disk and send data via network to other nodes (including failure handling and recovering) âą Implement and integrate algorithms for high availability of the cluster âą Investigate flaws in data consistency algorithms, requiring thorough debugging on multi-node cluster and in low-level byte represented data
đŻ Requirements
âą 4+ years experience in Java programming âą Deep knowledge of concurrency in Java and Java Memory Model and/or of concurrency model in other programming systems âą Excellent Java SE knowledge including IO, JVM internals, etc. âą Experience with SQL databases âą Experience in troubleshooting Java applications and/or databases âą English â upper-intermediate or higher âą Experience with NoSQL and/or distributed databases (strong plus) âą Experience with building highload distributed systems and algorithms (strong plus) âą Experience with Docker, Kubernetes and/or public Cloud (AWS, GCE, Azure, etc.) (strong plus)
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