Lead, Site Reliability Engineering

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Lead, Site Reliability Engineering

Site Reliability Engineer (SRE) - Generalist

Role

Summary:

The Site Reliability Engineer (SRE) - Generalist is a senior level engineer and cross stack reliability expert who proactively ensures system stability, performance, and operational resilience by deeply understanding application behavior and how it manifests across infrastructure. This role emphasizes anticipation over reaction. While the SRE Generalist participates in incident response, their primary value is in converting operational signals, incidents, and patterns into preventative actions-improving observability, reducing risk, and eliminating classes of failure before they impact customers.

They partner closely with application, platform, and infrastructure teams to continuously reduce mean time to detect (MTTD), mean time to resolve (MTTR), and overall incident frequency through data driven insight, automation, and engineering rigor.

• Anticipate reliability risks by analyzing application behavior, system signals, and historical incidents to identify failure patterns and systemic weaknesses before they result in outages.
• Translate deep application knowledge into reliability requirements, architectural guidance, and infrastructure improvements that prevent incidents rather than simply respond to them.
• Continuously assess system health, resiliency gaps, and operational debt, driving improvements that increase service robustness over time.

• Participate in and lead troubleshooting efforts during high severity and cross domain incidents, applying structured, data driven investigation techniques.
• Use incidents as learning opportunities-performing root cause analysis that focuses on why systems allowed failure, not just what broke.
• Ensure incident outcomes result in concrete, measurable improvements such as better instrumentation, safer defaults, automation, or architectural changes.

• Proactively design and evolve observability strategies by onboarding new data sources and improving signal quality across logs, metrics, traces, and events.
• Build dashboards, alerts, and monitors that surface early indicators of degradation, not just failure states.
• Apply analytical techniques to detect emerging trends, weak signals, and anomalous behavior before customers are impacted.
• Communicate insights through clear data storytelling that enables engineering teams and leaders to act decisively and early.

• Lead automation efforts that reduce manual intervention, shorten feedback loops, and eliminate repetitive operational work.
• Convert operational learnings into reusable tools, standards, documentation, and patterns that raise the reliability baseline across teams.
• Actively reduce operational toil and risk by improving system defaults, guardrails, and self healing capabilities.

• Partner across application, infrastructure, and platform teams to drive shared ownership of reliability outcomes and proactive operational thinking.
• Influence design and delivery decisions by representing the reliability perspective early in the development lifecycle.
• Mentor engineers by modeling proactive troubleshooting, systems thinking, and data driven decision making.

• Strong ability to reason about systems end to end, connecting application behavior to infrastructure performance and failure modes.
• Expertise in observability, monitoring, and troubleshooting tools, with a focus on signal quality and actionable insight.
• Proficiency in scripting and automation to operationalize reliability improvements and accelerate learning.
• Broad infrastructure knowledge (networking, Linux, databases, containers, storage), with depth in at least one domain.
• Strong data analysis and storytelling skills, enabling proactive identification of risks and clear…