Staff Software Engineer (Data/Infrastructure)

• Strong experience building or operating large-scale data infrastructure or analytics systems
• Hands-on background with distributed systems, databases, or query engines
• Experience scaling systems to support high-volume, multi-tenant workloads
• Deep interest in performance: profiling, tuning, and understanding systems end-to-end
• Practical experience working with open-source data technologies
• Proficiency in one or more systems or backend languages (Rust, C++, Java, Python)
• Comfortable making architectural tradeoffs and shipping incrementally rather than via big rewrites

• Competitive salary up to $250k plus sizeable equity
• Work on genuinely hard distributed systems and data problems
• High ownership and direct influence over core architecture
• Opportunity to scale a real production platform by orders of magnitude
• Collaborative, low-bureaucracy engineering culture

You’ll help design and build the core analytical data platform that powers a rapidly scaling, multi-tenant product handling telemetry and time-series data at massive scale.

The system already exists and is live - your work will focus on evolving it to support 10-100x growth without disruptive rewrites. This includes moving from a single primary data store toward a more flexible lakehouse-style architecture, building scalable ingestion pipelines, and implementing new compute layers that run efficiently over data in object storage.

You’ll spend a lot of time deep in the system: profiling performance, tuning query engines, optimizing memory usage, and making architectural tradeoffs that balance short-term delivery with long-term scalability. This is a hands-on role where you’ll ship production code, influence architectural direction, and help shape how the platform evolves over the next several years., This is a high-growth engineering company building infrastructure for data-intensive, mission-critical systems. The product sits at the intersection of analytics, observability, and complex real-world systems, and is used by customers who generate large volumes of high-value telemetry data.

The team is collaborative and highly technical. They rely heavily on proven open-source technology and care deeply about correctness, performance, and operational simplicity. The problems being solved are well understood in the industry - the challenge is executing them cleanly, efficiently, and at scale.