Senior Software Engineer - Distributed Systems (Continuous Profiler)

Datadog, Inc.; Paris; Hybrid; EUR 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Datadog, Inc. is seeking a distributed systems engineer to design and build core profiling services that process, index and store data at scale.

You’ll work with runtime engineers, data scientists and designers to deliver high-performance systems used for profiling in production. You will participate in multi-disciplinary squads, iterate with customers, and own code from development to production while meeting ambitious SLOs and quality gates.

Qualifications

• Experience with Java and/or Go is essential.
• Experience building high-performance, large-scale distributed systems.
• Excellent communication skills in English.
• Ability to review architectural proposals and guide trade-offs in a complex product space.
• Experience working with AI coding agents to produce performant and maintainable results.
• Strong collaborative skills across multidisciplinary teams.

Responsibilities

• Design, build and contribute to core profiling services at scale.
• Participate in multi-disciplinary squads and iterate with customers from exploration to product experiences.
• Own code from development to production, meeting ambitious SLOs and quality gates.
• Collaborate with UI, agentic tools, internal applications, integrations and partner products.

Skills

Java

Go

Distributed systems

High performance

English communication

AI agents

Collaboration

Job description

The Continuous Profiler ( https://www.datadoghq.com/blog/continuous-profiling-fourth-pillar/ ) team at Datadog is building a cutting-edge continuous profiling product that has low enough overhead to run continuously in production, unlocking insights into how customer applications perform under real workloads at scale. As AI reshapes software development and teams lose touch with how their code works and interacts with the hardware, this capability is becoming more essential than ever, for humans and AI alike. Today the information produced by our profilers is used for everything from automatic performance tuning to root cause analysis.

As a distributed systems engineer on the profiling team, you will be contributing to the systems that intake, process, index, store and make sense of the data collected. You will be working with some of the best runtime engineers, visualization experts, data scientists and designers in the industry on challenging and fun problems. Together, we contribute to runtime ecosystems such as Go ( https://opensource.datadoghq.com/projects/go/ ) and tackle novel problems, from profiling asynchronous Python applications ( https://www.datadoghq.com/blog/engineering/async-python-profiler/ ) to helping customers solve memory leaks in their applications ( https://www.datadoghq.com/blog/memory-leak-workflow/) .

At Datadog, we place value in our office culture: the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

What You'll Do:

• Help design, build and contribute to the core services making the profiling product possible, at a scale that is unusual even within Datadog.
• Participate in multi-disciplinary squads, and iterate with customers, to bring ideas all the way from early explorations to impactful product experiences.
• You will be responsible for your code from development to production, and meet ambitious SLO and quality gates.
• You will be working with many internal and external stakeholders, working on various ways to consume the profiling data, such as the UI, agentic tools, internal applications, integrations and partner products.

Who You Are:

• Experience with Java and/or Go essential.
• Distributed systems engineer with experience building high performance large scale systems.
• Excellent communication skills (English).
• Ability to meaningfully review architectural proposals and guide technical trade-offs in a complex product space.
• Experience working with AI coding agents to produce performant and maintainable results.
• Experience collaborating