About the OpportunityWe are partnering with a leading quantitative trading firm seeking an experienced Storage Infrastructure Engineer to join its Data Engineering Infrastructure team in Chicago.This is a hands-on engineering role focused on building, scaling, and maintaining the large-scale storage and data infrastructure supporting high-frequency trading and quantitative research operations.The position involves working directly with on-premises infrastructure, Linux systems, distributed storage technologies, and enterprise storage platforms. As the firm's data requirements continue to grow, this engineer will contribute to the performance, reliability, and scalability of its underlying storage environment.Key ResponsibilitiesDesign, deploy, and operate large-scale data storage infrastructure, including Hadoop, enterprise storage, and S3-compatible platforms.Build, maintain, and scale on-premises storage systems supporting data-intensive workloads.Tune Linux systems for I/O throughput, performance, and reliability.Automate infrastructure configuration and deployment using Ansible, Puppet, or similar automation tools.Implement monitoring and observability using Prometheus and related technologies.Partner with engineering teams to deliver reliable, well-architected data solutions, with a focus on storage and Kafka.Contribute to storage architecture, capacity planning, and infrastructure scalability.Work with distributed storage technologies and support the continued development of the firm's data infrastructure.Required Skills & Experience5+ years of experience in systems engineering, with a strong focus on data storage infrastructure.Strong Linux fundamentals, including debugging, troubleshooting, and performance tuning for I/O throughput.Hands-on experience building, implementing, operating, or scaling storage systems.Experience working with on-premises infrastructure and distributed storage environments.Hands-on experience with Ansible and Puppet for configuration management and automation.Familiarity with open-source, S3 API-compliant, and enterprise storage technologies.Working knowledge of the Hadoop ecosystem, including YARN.Experience with Java and Python.Experience with Prometheus-based monitoring and alerting.Familiarity with Kubernetes.Comfort working with AI-assisted development tools in an enterprise environment.
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About the OpportunityWe are partnering with a leading quantitative trading firm seeking an experienced Storage Infrastructure Engineer to join its Data Engineering Infrastructure team in Chicago.This is a hands-on engineering role focused on building, scaling, and maintaining the large-scale storage and data infrastructure supporting high-frequency trading and quantitative research operations.The position involves working directly with on-premises infrastructure, Linux systems, distributed storage technologies, and enterprise storage platforms. As the firm's data requirements continue to grow, this engineer will contribute to the performance, reliability, and scalability of its underlying storage environment.Key ResponsibilitiesDesign, deploy, and operate large-scale data storage infrastructure, including Hadoop, enterprise storage, and S3-compatible platforms.Build, maintain, and scale on-premises storage systems supporting data-intensive workloads.Tune Linux systems for I/O throughput, performance, and reliability.Automate infrastructure configuration and deployment using Ansible, Puppet, or similar automation tools.Implement monitoring and observability using Prometheus and related technologies.Partner with engineering teams to deliver reliable, well-architected data solutions, with a focus on storage and Kafka.Contribute to storage architecture, capacity planning, and infrastructure scalability.Work with distributed storage technologies and support the continued development of the firm's data infrastructure.Required Skills & Experience5+ years of experience in systems engineering, with a strong focus on data storage infrastructure.Strong Linux fundamentals, including debugging, troubleshooting, and performance tuning for I/O throughput.Hands-on experience building, implementing, operating, or scaling storage systems.Experience working with on-premises infrastructure and distributed storage environments.Hands-on experience with Ansible and Puppet for configuration management and automation.Familiarity with open-source, S3 API-compliant, and enterprise storage technologies.Working knowledge of the Hadoop ecosystem, including YARN.Experience with Java and Python.Experience with Prometheus-based monitoring and alerting.Familiarity with Kubernetes.Comfort working with AI-assisted development tools in an enterprise environment.
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