Staff Software Engineer – Logs Observability Pipelines

Datadog
New York, New York, USAPosted 23 March 2026

Job Description

Datadog is seeking a Staff Software Engineer to help shape the future of our Bring Your Own Cloud (BYOC) Logs offering by unifying observability pipelines and on-prem log management into a seamless customer experience. This role will focus on building and scaling systems that process, route, and store high-volume observability data within customer-managed infrastructure. You will operate as a hands-on technical leader, driving architecture, cross-team delivery, and product direction across a complex and evolving space. This is a high-impact opportunity to influence product strategy, mentor engineers, and solve deeply technical challenges at scale. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Drive the architecture and technical direction for unifying observability pipelines and on-prem observability storage into a cohesive BYOC Logs experience Build and scale high-throughput systems for log processing, routing, and transformation across distributed environments Lead cross-team initiatives, aligning engineers, product managers, and stakeholders to deliver complex, multi-team projects Design and implement software that runs reliably within customer-managed infrastructure, including on-prem and cloud environments Improve system performance, scalability, and cost efficiency through thoughtful trade-off analysis and capacity planning Contribute hands-on to critical code paths, debugging, and deployment challenges in customer environments Who You Are: You have experience building and operating software deployed in customer-managed or on-prem environments, not just SaaS platforms You have strong expertise in distributed systems, including scalability, performance optimization, and high-throughput data processing You are proficient in systems-level programming (e.g., Go, Rust, or C++) and understand how software runs across diverse environments (e.g., Linux systems) You have experience with cloud platforms (e.g., AWS, Azure, or GCP) and are comfortable troubleshooting infrastructure and networking issues You are experienced with containerization and orchestration technologies such as Kubernetes in production environments You have a track record of leading large, cross-functional engineering efforts and influencing technical direction across teams Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: Generous and competitive benefits package New hire stock equity (RSUs) and employee stock purchase plan Continuous career development and pathing opportunities Employee-focused best in class onboarding Internal mentor and cross-departmental buddy program Friendly and inclusive workplace culture Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-Hybrid Datadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan. The reasonably estimated yearly salary for this role at Datadog is: $234,000 $300,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity ... (truncated, view full listing at source)
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