Senior Site Reliability Engineer – SRE

🕒 August 4

🇪🇸 Spain – Remote

💵 €70k - €115k / year

⏰ Full Time

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 0%

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QAD

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1979

🏭 Manufacturing

📦 Logistics

🍽️ Food & Beverage

Manufacturing • Logistics • Food & Beverage

QAD is a company specializing in enterprise resource planning and industrial transformation solutions. Their Adaptive Enterprise platform helps businesses optimize processes, align people with technology, and manage critical business challenges. QAD's offerings include software for manufacturing, inventory management, supply chain planning, quality management, and global trade compliance. Their solutions serve a range of industries, including automotive, consumer products, food and beverage, industrial manufacturing, and more. The company focuses on becoming an adaptive enterprise by integrating advanced scheduling and data-driven insights.

📋 Description

• Design, implement, and maintain highly available, scalable, and resilient systems • Serve as a subject matter expert for observability, including monitoring, alerting, logging, tracing, dashboards, and synthetic testing • Develop maintainable software and self-service tooling to automate operational tasks and improve reliability • Identify and eliminate operational toil through automation, process improvements, and systematic problem solving • Lead incident response, participate in on-call rotations, and drive blameless post-mortems • Define, implement, and track SLIs, SLOs, and error budgets • Leverage infrastructure as code, GitOps practices, and CI/CD automation using Terraform, Flux, and GitHub Actions • Provide reliability expertise during system design reviews and influence architectural decisions • Document processes, build runbooks, and mentor engineers across the organisation • Use AI responsibly to accelerate investigations, improve documentation, reduce toil, and build intelligent operational workflows • Collaborate across infrastructure, applications, networking, identity, and observability domains • Drive meaningful follow-up actions and continuous reliability improvements

🎯 Requirements

• Demonstrated experience operating and improving production systems at scale in an SRE, Production Engineering, or Platform Engineering role • Ability to build accurate mental models of complex distributed systems across infrastructure, applications, networking, identity, and observability • Strong troubleshooting skills and evidence-driven incident response and root cause analysis • Experience defining and using SLIs, SLOs, and error budgets • Excellent written and verbal communication skills • Experience with Kubernetes, including Amazon EKS, and service mesh technologies such as Istio • Experience with AWS cloud infrastructure and services • Experience with identity and access management systems, including Auth0 and AWS IAM • Knowledge of DNS, load balancing, routing, TLS, and connectivity troubleshooting • Experience with GitOps workflows and infrastructure automation using Flux and Terraform • Experience with observability platforms and practices, including metrics, logs, traces, alerting, dashboards, and synthetic monitoring • Experience with CI/CD systems and engineering workflows • Experience with application logging and distributed system debugging • Strong scripting and automation skills • Ability to build and maintain automation, tooling, and self-service capabilities using Python, Go, or Bash • Ability to remain calm and effective during high-severity incidents • Ability to manage complex situations involving multiple teams and competing priorities • Ability to lead blameless post-mortems and drive follow-up actions • Effective use and validation of AI assistants for troubleshooting, root cause analysis, and operational decision-making

🏖️ Benefits

• Fully remote work • Opportunities for growth • Equal opportunity and inclusive work environment • Diversity, equity, and inclusion program • Human oversight, security, and governance when using AI