Software Engineer; Data​/Infrastructure

Senior Data Infrastructure Engineer – Distributed Analytics at Scale

What You’ll Do:

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.

• 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

• 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