Senior Observability Platform Engineer

Lighthouse Technology Services is partnering with our client to fill their Senior Observability Platform Engineer position! This is a 10+ months contract with potential to hire. Preference is for someone to work hybrid in Buffalo, NY for conversion purposes, but is also open to contract remote in United States. This role will be a W2 employee of Lighthouse Technology Services. No C2C or subcontracting arrangements will be considered.

What You’ll Be Doing:

• Lead hands-on technical leadership for observability platform reliability and scalability across enterprise monitoring systems, including Dynatrace and IBM SevOne
• Design and enforce observability patterns, standards, and data models to ensure alignment across multiple observability tools (Dynatrace, IBM SevOne, ServiceNow ITOM)
• Drive AIOps enablement initiatives, including Davis AI implementation and causal analysis capabilities to improve operational decision-making
• Architect and scale observability platforms across Application Performance Monitoring, Network Performance Monitoring, and Ingest (Dashboard & Visibility) tiers
• Prevent uncontrolled log growth, reduce alert noise, and implement cost optimization strategies across the observability ecosystem
• Lead root cause analysis initiatives and provide critical support during incident response “war room” sessions
• Manage system health monitoring for servers, infrastructure, and applications across the enterprise
• Collaborate with cross-functional teams to implement intelligent automation and advance observability maturity across the organization

• 8+ years of engineering experience with demonstrated expertise in both engineering and architecture roles
• Deep expertise in designing and scaling enterprise observability platforms such as Dynatrace, DataDog, IBM SevOne, or similar tools
• Proven ability to define and enforce observability patterns, standards, and data models at scale
• Strong experience leading intelligent automation and root cause analysis initiatives within observability environments
• Hands-on experience with AIOps platforms and AI-driven analysis tools (e.g., Davis AI, causal analysis engines)
• Demonstrated expertise in managing observability data (logs, metrics, alerts) at scale with a focus on cost optimization and governance
• Solid understanding of platform reliability, scalability, and cross-tool integration in complex enterprise environments
• Strong analytical and problem-solving skills with the ability to operate effectively during high-pressure incident response scenarios