The opportunity
Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever.
What you'll do
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.
What they're looking for
- 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.
- + 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).
