Data Engineer - Infrastructure

Fintal Partners; Chicago (IL); On-site; USD 130,000 - 180,000; Full time

Job summary

Fintal Partners, a Chicago-based quantitative trading firm, seeks an experienced Storage Infrastructure Engineer to join its Data Engineering Infrastructure team. The role focuses on building, scaling, and maintaining large-scale storage and data infrastructure to support high-frequency trading and quantitative research operations.

You will work with on-premises Linux systems, distributed storage environments, and enterprise storage platforms to drive performance, reliability, and scalability.

Qualifications

• 5+ years in systems engineering focusing on data storage infrastructure.
• Strong Linux fundamentals including debugging, troubleshooting, and I/O performance tuning.
• Hands-on experience building, implementing, operating, or scaling storage systems.
• Experience 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-compatible, and enterprise storage technologies.
• Knowledge of 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.

Responsibilities

• Design, 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 tools.
• Implement monitoring and observability using Prometheus and related technologies.
• Partner with engineering teams to deliver reliable data solutions focusing on storage and Kafka.
• Contribute to storage architecture, capacity planning, and infrastructure scalability.
• Work with distributed storage technologies and support ongoing development of the firm’s data infrastructure.

Skills

Linux basics

Storage systems

Performance tuning

Data infrastructure

Troubleshooting

Tools

Ansible

Puppet

Prometheus

Kubernetes

Java

Python

Job description

We 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 Responsibilities

• Design, 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 & Experience

• 5+ 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.