Site Reliability Engineer (TechOps)

Our client, a leading organization in the banking and financial services industry, is looking for a Site Reliability Engineer(TechOps) to join their Private Client Technology team. The role focuses on improving system reliability and performance through software development, automation and infrastructure operations. The ideal candidate will have a solid software development, automation and infrastructure operations. The ideal candidate will have a solid development background, particularly in C#/.NET, along with experience in Microsoft Azure and Infrastructure as Code.

You'll play a key role in automating processes, reducing operational risks and ensuring systems remain reliable, resilient and scalable.

Requirements

• **1.

• Software engineering for reliability

• Understand, troubleshoot, and improve C#/.NET application code, with a focus on production behaviour,

• failure modes, and supportability.

• Build automation, utilities and reusable engineering patterns that remove toil and improve consistency,

• recovery, and developer experience.

• Apply modern engineering practices including version control, peer review, testing, secure coding, and

• maintainable design.

• 2. Azure and cloud engineering

• Engineer and support reliable services on Microsoft Azure using cloud-native capabilities and sound

• operational practices.

• Contribute to resilient, scalable, and cost-aware cloud designs across application and platform layers.

• Identify cloud reliability risks and implement practical improvements that strengthen service operability and

• recovery.

• 3. CI/CD, infrastructure as code and GitOps

• Design, improve and support CI/CD pipelines and deployment automation so releases are repeatable,

• observable, and safe.

• Create and maintain infrastructure as code using Terraform, Bicep, ARM templates, or comparable tooling.

• Use GitOps principles to manage infrastructure and application configuration through version control and

• automated deployment.

• 4. Monitoring, observability, and alerting

• Implement and improve application and infrastructure telemetry using logs, metrics, traces, dashboards,

• and actionable alerts.

• Use observability data to detect, diagnose, and resolve production issues and identify reliability trends and

• risks.

• Work with platforms such as Dynatrace, Datadog, New Relic, Splunk, Grafana or equivalent technologies.

• 5. Production engineering and continuous improvement

• Participate in production troubleshooting and incident response using evidence-led diagnosis and clear

• technical communication.

• Turn incident learning into engineering actions that improve reliability, resilience, scalability, and

• performance.

• Define and use service-level indicators and objectives, improve runbooks and operational readiness, and

• support tested recovery practices.

• **Qualifications, Experience and Skills

• Strong to intermediate hands-on C#/.NET development experience, including understanding and

• troubleshooting production application code.

• Practical cloud experience, with Microsoft Azure strongly preferred and weighted more highly.

• Good understanding of CI/CD, deployment automation, and modern software delivery practices.

• Hands-on infrastructure-as-code experience using Terraform, Bicep, ARM templates, or similar tooling.

• Practical monitoring, observability, and alerting experience, with working knowledge of GitOps and

• production troubleshooting.

• Advantageous but not exclusionary: AKS/Kubernetes, Docker, event-driven architectures, messaging,

• distributed systems, and performance engineering.

• Proficiency in using AI-enabled productivity tools, such as Copilot, to improve efficiency, generate insight

• and support decision-making. Applies critical thinking and sound judgement when interpreting outputs,

• remains accountable for the quality and accuracy of their work

• **SUCCESS MEASURES

• **Reliability & resilience- Services meet agreed reliability objectives, recover predictably, and show fewer repeat

• failures.

• Operational toil- Manual, repetitive work is reduced through safe automation, self-service, and reusable

• engineering patterns.

• Observability - Actionable telemetry, dashboards, and alerts improve detection, diagnosis, and service

• understanding.

• Delivery engineering- Deployment processes are repeatable, version-controlled, and increasingly automated.

• Developer experience- Delivery teams adopt practical reliability patterns, runbooks, and cloud engineering

• standards.

• Production readiness- Services have usable operational information, tested recovery practices, and clear production

• supportability.