Data Engineer, Infrastructure

Selby Jennings; Chicago (IL); On-site; USD 120,000 - 160,000; Full time

Job summary

Selby Jennings is assisting a high-performance trading technology firm in finding a Data Infrastructure Engineer. You will design, deploy, and scale storage platforms and data pipelines across the business, with focus on latency-sensitive workloads and data-intensive apps.

You will optimize Linux environments, automate infrastructure with Ansible or Puppet, and implement robust monitoring. Kubernetes and Kafka experience is essential for this role.

Qualifications

• 5+ years in infrastructure, systems, or platform engineering focused on storage.
• Strong Linux admin, troubleshooting, and performance tuning.
• Hands-on with infrastructure-as-code and CM tools (Ansible or Puppet).
• Knowledge of distributed storage and enterprise storage environments.
• Experience supporting large-scale data platforms and big data ecosystems.
• Programming or scripting in Python, Java, or similar.
• Familiarity with observability/monitoring solutions (Prometheus).
• Experience in automated engineering environments and AI-assisted tools.
• Exposure to Kubernetes.

Responsibilities

• Architect, deploy, and maintain large-scale storage platforms, including distributed storage systems, object storage environments and data lake environments.
• Optimize Linux systems for storage efficiency, throughput, and overall performance.
• Develop and enhance infrastructure automation using tools such as Ansible, Puppet, or similar frameworks.
• Implement monitoring, alerting, and observability solutions to improve platform reliability and operational visibility.
• Collaborate with software and platform engineering teams to deliver scalable data infrastructure solutions.
• Support and enhance data streaming and messaging technologies, including Kafka-based environments.
• Contribute to containerized infrastructure initiatives leveraging Kubernetes and related technologies.

Skills

Linux administration

Python/Java scripting

Infrastructure automation

Distributed storage knowledge

Big data platforms

Observability

Tools

Ansible

Puppet

Prometheus

Kafka

Kubernetes

Job description

Our client, a high-performance technology-driven trading firm, is seeking a Data Infrastructure Engineer to help evolve and scale the platforms that support large-scale data storage, processing, and distribution across the business. This role is ideal for an engineer who enjoys working deep within Linux environments, optimizing system performance, and building highly reliable infrastructure from the ground up.

As data volumes continue to expand, you will play a critical role in designing, automating, and maintaining the storage ecosystem that supports latency-sensitive workloads and data-intensive applications.

Responsibilities

• Architect, deploy, and maintain large-scale storage platforms, including distributed storage systems, object storage solutions, and data lake environments
• Optimize Linux systems for storage efficiency, throughput, and overall performance
• Develop and enhance infrastructure automation using tools such as Ansible, Puppet, or similar frameworks
• Implement monitoring, alerting, and observability solutions to improve platform reliability and operational visibility
• Collaborate with software and platform engineering teams to deliver scalable data infrastructure solutions
• Support and enhance data streaming and messaging technologies, including Kafka-based environments
• Contribute to containerized infrastructure initiatives leveraging Kubernetes and related technologies

Requirements

• 5+ years of experience in infrastructure, systems, or platform engineering with a focus on storage technologies
• Strong expertise in Linux administration, troubleshooting, and performance tuning
• Hands‑on experience with infrastructure-as-code and configuration management tools such as Ansible or Puppet
• Knowledge of distributed storage platforms, object storage technologies, and enterprise storage environments
• Experience supporting large-scale data platforms and big data ecosystems
• Programming or scripting experience with Python, Java, or similar languages
• Familiarity with modern observability and monitoring solutions, including Prometheus
• Experience working within highly automated engineering environments and leveraging AI-assisted development tools
• Exposure to container orchestration platforms such as Kubernetes

Preferred Background

• Experience supporting large-scale data pipelines, analytics infrastructure, or real-time data environments
• Familiarity with high-performance computing, low-latency infrastructure, or financial technology environments
• Understanding of distributed systems architecture and scalability best practices