Cloud / Infrastructure Engineer

Product Line Overview (Flight Data Intelligence)

Acron Aviation’s Flight Data Intelligence (FDI) organization provides advanced flight data analytics, safety insights, and operational intelligence solutions to aircraft operators worldwide. Through a combination of aviation expertise, data science, and cloud-based technology, FDI helps customers improve safety, compliance, operational efficiency, and fleet performance. Our teams work closely with airlines, operators, OEMs, and regulators to transform aviation data into actionable intelligence that supports safer skies and better operational outcomes.

Job Title

Cloud / Infrastructure Engineer – AWS & Terraform

Position Summary

We are seeking a Cloud / Infrastructure Engineer to own AWS infrastructure and Infrastructure-as-Code that enables application teams to deploy, operate, and scale Flight Data Intelligence services reliably.

This is an infrastructure-first role focused on Terraform, AWS resource ownership, and CI/CD delivery pipelines. The role is not centered on application feature or API development, but on ensuring that services can be deployed safely, consistently, and operated in production with confidence.

You will work closely with engineering, product, and operations teams to build and maintain scalable, secure, and highly available cloud environments supporting aviation analytics platforms used by customers worldwide.

Infrastructure and Cloud Ownership

• Design, provision, and maintain AWS infrastructure using Terraform to support analytics services
• Own Terraform modules, environment separation (development, staging, production), and state management practices
• Implement and evolve AWS resources, including IAM, networking, compute, storage, and service integrations
• Ensure infrastructure changes are repeatable, auditable, and production-safe
• Design, deploy, and manage Amazon EKS clusters

CI/CD and Delivery Responsibility

• Design, maintain, and improve CI/CD pipelines supporting build, test, and deployment workflows
• Own deployment reliability, environment promotion, and rollback strategies
• Diagnose and resolve infrastructure-related and deployment-related failures within CI/CD pipelines and production environments
• Partner with application engineering teams to improve deployment workflows and reduce operational risk

Operational Readiness and Collaboration

• Integrate infrastructure with monitoring, logging, alerting, and observability systems
• Support production operations and participate in incident response activities related to infrastructure and deployments
• Collaborate with backend and data engineering teams to enable scalable and reliable service operation
• Develop and maintain operational documentation, procedures, and support runbooks
• Utilize observability data to identify issues and drive corrective actions

Required Qualifications

• 5+ years of experience in cloud, infrastructure, or DevOps engineering roles
• Hands-on ownership of AWS infrastructure in production environments
• Strong experience with Infrastructure-as-Code, specifically Terraform
• Experience designing and owning CI/CD pipelines and deployment workflows
• Practical understanding of cloud networking, IAM, and security principles
• Experience supporting production systems and resolving infrastructure or deployment issues
• Strong collaboration and communication skills when working with cross-functional engineering teams
• Working knowledge of Kubernetes or experience supporting EKS-based platforms

Preferred Additional Skills

• Experience supporting cloud-based SaaS or data-intensive platforms
• Familiarity with Docker-based deployments
• Experience integrating infrastructure with monitoring, logging, and observability tooling
• Exposure to regulated, safety-critical, or data-sensitive environments
• Experience with GitLab CI or similar CI/CD platforms
• Familiarity with Jira and Confluence
• Knowledge of aviation analytics, flight operations, or aviation technology environments

Technologies Used (For Context; Not All Required)

• AWS (EKS, Lambda, IAM, networking, compute, storage, and service integrations)
• Terraform
• CI/CD platforms (GitLab CI preferred)
• Docker
• Kubernetes
• Monitoring, observability, and logging tools
• Jira
• Confluence

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.