Q1 Technologies, Inc.
Site Reliability Engineer
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SRE with Python
Location: London, UK
Job Overview
We are seeking a Site Reliability Engineer (SRE) with deep Python expertise to bridge the gap between software development and systems operations. In this role, you will apply standard software engineering practices to infrastructure challenges, focus heavily on automation, and build highly scalable, self-healing systems. Your primary mission is to optimize system performance, maximize service uptime, and eliminate manual toil using Python-driven tooling.
Key Responsibilities
Automation & Tooling
- Build custom internal tools, APIs, and automation scripts using Python to streamline operational workflows.
- Eliminate operational toil by writing self-healing scripts that automatically diagnose and resolve standard infrastructure alerts.
- Develop and maintain CI/CD pipelines using Jenkins, GitLab CI, or GitHub Actions to ensure safe, rapid software delivery.
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System Reliability & Architecture
- Own system availability, latency, performance, and capacity management across cloud environments.
- Define, monitor, and enforce Service Level Indicators (SLIs) and Service Level Objectives (SLOs) while effectively managing error budgets.
- Review system architecture alongside development teams to ensure new features are built for scalability and fault tolerance.
Incident Management & Observability
- Participate in on-call rotations to provide primary operational support for large-scale distributed applications.
- Design observability dashboards using tools like Prometheus, Grafana, Datadog, or the ELK stack to track the 4 Golden Signals.
- Lead blameless post-mortems and perform Root Cause Analysis (RCA) to prevent recurring infrastructure failures.
Required Skills & Qualifications
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Technical Skills
- Advanced Python Proficiency: Expert-level knowledge of Python (OOP principles, data structures, and asynchronous programming) along with frameworks like FastAPI, Flask, or Django.
- Infrastructure as Code (IaC): Hands-on experience with Terraform, Ansible, or Pulumi for automated provisioning.
- Containerization: Proven experience managing containerized workloads at scale using Docker and Kubernetes.
- Cloud Architecture: Deep operational experience with at least one major cloud provider, such as AWS, Google Cloud Platform (GCP), or Microsoft Azure.
- Systems & Networking: Strong understanding of Linux system administration (RHEL/Ubuntu), process management, and networking fundamentals (TCP/IP, DNS, HTTP, SSL/TLS).
- Databases: Solid working knowledge of relational databases (PostgreSQL, MySQL) and NoSQL stores.
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