Staff Engineer, Observability — Scale & Reliability

MongoDB; Ireland; Hybrid; EUR 180,000 - 240,000; Full time

Job summary

MongoDB is seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. You will lead architecture for metrics, logs, traces, and alerts while collaborating with SWE, Product and SRE teams.

The role is based in Dublin with a hybrid work model and a strong emphasis on technical leadership and high standards. You will work on systems handling billions of metrics and petabytes of data using VictoriaMetrics, Splunk, Flink,

Qualifications

• 10+ years of experience designing, programming, debugging, and tuning distributed and highly concurrent software systems (C/C++, Java, Rust, or Go).
• Experience running latency‑sensitive, high throughput systems.
• Strong systems fundamentals: multi‑threaded programming, performance profiling.
• Familiarity with observability ecosystem and best practices.
• Excellent communication and mentorship skills.

Responsibilities

• Architect and build the mission‑critical observability platform components for performance, scalability, cost efficiency, and resiliency.
• Implement observability improvements for rapid root‑cause diagnosis of production issues.
• Handle production escalations and coach peers to resolve issues.
• Write production‑grade database code; improve and maintain quality and security.

Skills

C/C++

Java

Rust

Golang

Distributed systems

Multithreading

Observability

Performance tuning

Tools

VictoriaMetrics

Splunk

Flink

WarpStream

Kafka

Fluentbit

Job description

MongoDB is seeking a Staff engineer to design, build, and operate the internal and external Observability stack for the MongoDB platform. You will lead architecture for metrics, logs, traces, and alerts while collaborating with SWE, Product and SRE teams.

The role is based in Dublin with a hybrid work model and a strong emphasis on technical leadership and high standards. You will work on systems handling billions of metrics and petabytes of data using VictoriaMetrics, Splunk, Flink,