Staff Software Engineer, Amplitude

• This role is ideal for someone who finds real satisfaction in making a complex distributed system faster, cheaper, and more reliable — and who wants to do that work on a system that directly powers the product experience for thousands of customers
• Gets energy from working deep inside a complex distributed system — understanding how data flows through it, where the bottlenecks are, and how to make it meaningfully better
• Has built or significantly extended an OLAP engine, columnar database, query processor, or large-scale data processing system — not just operated one
• Thinks about cost, performance, and reliability as interconnected concerns, not separate workstreams
• Communicates clearly about technical tradeoffs and earns influence through the quality of your work and ideas, not through title
• Finds it natural to help other engineers level up — through pairing, design reviews, or just being the person who explains the “why” behind a system’s design
• 7+ years of industry experience in backend or infrastructure engineering, with depth in distributed data systems
• Hands-on experience building or extending analytical/OLAP systems — query engines, columnar storage, large-scale data processing frameworks, or equivalent
• Track record of driving significant cost optimization on cloud infrastructure at scale (compute, storage, network)
• Strong computer science fundamentals: distributed systems (partitioning, replication, consistency, failover), data structures and algorithms, concurrency and multi-threading, performance optimization
• Production experience with modern cloud infrastructure — AWS (S3, DynamoDB, EC2), Kafka, Redis/ElastiCache, Kubernetes, Terraform — or strong equivalents
• Proficiency in Java, C++, or Python
• Demonstrated technical influence beyond your immediate team: leading design discussions, driving cross-team alignment, mentoring engineers

Desirable

• We’re looking for a Staff Software Engineer who wants to go deep on both the engine internals and the infrastructure underneath it
• You’ll work across the full stack of a modern OLAP system — query planning and execution, columnar storage and encoding, distributed compute, caching, and cloud infrastructure — while driving meaningful improvements to performance, cost-efficiency, and reliability at scale
• You’ll influence technical direction through your work, your design reviews, and your mentorship of other engineers on a team of ~10
• Work across Nova's query execution engine and distributed compute layer: query planning, columnar storage formats, encoding and compression, caching, and cluster-level resource management
• Design and implement new capabilities as Nova expands to support more warehouse-imported data types, such as metrics, profiles, and dimensions
• Design for high-throughput automated query workloads — as AI agents become a primary source of queries, ensure Nova’s architecture supports sustained, concurrent, and programmatic query patterns at scale
• Own and execute projects that materially reduce infrastructure cost — compute, storage, network, and memory — while maintaining or improving latency and throughput
• Profile and optimize JVM performance: GC tuning, memory management, concurrency, and data layout decisions that compound at our scale
• Build guardrails and observability to catch expensive or pathological queries before they impact the system
• Strengthen Nova’s reliability posture: identify systemic failure modes, drive durable fixes, and raise the bar on how we detect and respond to production issues
• Participate in on-call rotation to root-cause incidents and turn one-off fixes into architectural improvements
• Contribute to capacity planning, safe rollout practices, and the operational tooling that keeps Nova healthy
• Lead the design and execution of multi-month projects that improve Nova’s architecture, performance, or capabilities
• Contribute to technical direction through design docs, architecture discussions, and code reviews — helping the team make principled tradeoffs
• Mentor senior engineers on distributed systems thinking, production debugging, and system design
• Collaborate with Product, Middleware, Data Pipeline, and other engineering teams to ensure Nova’s capabilities translate into customer value