Lead Site Reliability Engineer

About the role

LSEG is evolving its Site Reliability Engineering capabilities within its Markets and Risk Intelligence division. As a Technical Lead SRE, you will be a senior hands-on expert who helps build the foundations of reliability across new and existing platforms, working with Architecture, Engineering, Security and Platform teams. It is not a people-management or shift-based role, but you will work closely with global teams and may be called out for major incidents.

Key responsibilities

• Lead the establishment of SRE foundations for new projects: environments, monitoring, alerting and operational readiness from day one.
• Embed reliability, scalability, security and observability into system design with Architecture and Engineering teams.
• Define and champion observability standards, tooling and guidelines across metrics, logs, traces and SLIs/SLOs.
• Design monitoring and alerting solutions that reduce toil and improve system health.
• Drive reliability improvements through incident reduction, performance tuning and resilient patterns.
• Partner with Security teams on compliance, security and risk expectations.
• Ensure smooth handover from project delivery to BAU SRE operations, with documentation and operational practices.
• Influence design decisions through cloud cost optimisation and efficiency initiatives.
• Mentor engineers, shape engineering standards and foster a culture of learning.

Required profile

• Bachelor's degree in Computer Science or a related field.
• 10+ years of hands-on technical experience in SRE, Platform Engineering, Infrastructure or similar roles.
• Strong technical authority, calm and methodical under pressure, pragmatic problem-solver and clear communicator.

Required skills

• Strong AWS experience (EKS, ECS, EC2, networking, IAM, managed services).
• Deep hands-on Kubernetes and Linux administration.
• Observability platforms, including Datadog for metrics, logs, APM and alerting.
• SRE principles: SLOs, error budgets, incident management.
• Cloud security and cloud cost optimisation.
• Integrating AI with observability stacks (Prometheus, Grafana, ELK, OpenTelemetry).
• Good to have: Azure, Terraform, vector databases, RAG, and generative AI platforms.