Job description

We are hiring an Engineer to join our Data Engineering Infrastructure team, where you will help build and scale the storage and data platforms that power our HFT business. This is a hands-on role for someone who enjoys working close to the bare metal systems. Operating large-scale open-source storage, enterprise storage, tuning Linux systems for performance, automating infrastructure. As our data footprint grows, you will play a key part in keeping our infrastructure fast, reliable, and ready to scale. Your Core Responsibilities: Design, deploy, and operate large-scale data storage infrastructure, including Hadoop, enterprise storage and S3-compatible platforms Tune Linux systems for I/O throughput and overall performance Automate configuration and deployment using Ansible, Puppet or other automation platform Build observability into the platform with Prometheus and related tooling Partner with engineering teams to deliver reliable, well-architected data solutions with a focus on Storage and Kafka Familiarity with Kubernetes Your Skills & Experience: 5+ years of experience in systems engineering with a strong focus on data storage Strong Linux fundamentals, debugging skills, including performance tuning for I/O throughput 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 in Java and Python Comfort working with AI-assisted development tools such as Claude in an enterprise setting Experience with Prometheus-based monitoring and alerting The Base Salary range for the role is included below. Base salary is only one component of total compensation; all full-time, permanent positions are eligible for a discretionary bonus and benefits, including paid leave and insurance. Please visit Benefits - US | IMC Trading for more comprehensive information. Salary Range $175,000 — $225,000 USD About Us IMC is a research-driven trading firm where quantitative modeling, machine learning, and engineering shape how modern markets are traded. A stabilizing force in markets since 1989, we provide liquidity across trading venues, delivering the best outcome in value and risk management to investors. Using our own technology and capital, we build proprietary systems and algorithms that operate across global markets. Our researchers, traders, and engineers work as a collective, combining rapid experimentation, advanced infrastructure, and real-time feedback to turn insight into execution and execution into advantage.

Requirements

Must-haves

Design, deploy, and operate large-scale data storage infrastructure, including Hadoop, enterprise storage and S3-compatible platforms
Tune Linux systems for I/O throughput and overall performance
Automate configuration and deployment using Ansible, Puppet or other automation platform
Build observability into the platform with Prometheus and related tooling
Partner with engineering teams to deliver reliable, well-architected data solutions with a focus on Storage and Kafka
Familiarity with Kubernetes
5+ years of experience in systems engineering with a strong focus on data storage
Strong Linux fundamentals, debugging skills, including performance tuning for I/O throughput
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 in Java and Python
Comfort working with AI-assisted development tools such as Claude in an enterprise setting
Experience with Prometheus-based monitoring and alerting

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

kubernetesapijavapythonaimachine learning

Platform: greenhouse
Effort: quick