Staff Software Engineer

• 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.

You are an experienced systems engineer who:

• 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.

• Experience with specific OLAP or query engine systems: Druid, ClickHouse, Presto/Trino, BigQuery, Snowflake, or similar.
• Deep JVM expertise — GC tuning, profiling, memory optimization at production scale.
• Experience with columnar data formats and encodings (Arrow, Parquet, ORC, or custom formats).
• Familiarity with product analytics, experimentation platforms, or event-driven data systems.
• Contributions to open-source data infrastructure projects or published work in the data systems space.

At Amplitude, our values guide how we show up for one another and for our customers:

• Humility: We operate from a place of empathy and openness, seeking to understand many points of view.
• Ownership: We take the initiative to solve problems that drive our shared company success.
• Growth Mindset: We’re tenacious in the face of challenges and seek feedback in order to grow ourselves and others.
• Customer Centricity: We put the customer at the center of everything we do and are deeply committed to their success.