SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Amplitude is a leading AI analytics platform serving over 4,700 customers including Atlassian, Burger King, NBCUniversal, and Square. The Analytics Compute Platform team owns the critical compute layer that powers all charts, insights, and experiment results across Amplitude's product suite.
As a Senior Software Engineer on this team, you'll design and build core components of the query and compute engine that translates user questions into fast, correct answers. You'll work at the intersection of performance, reliability, and flexibility—three goals that are often in tension and create interesting engineering challenges.
Key responsibilities include:
- Design and build core parts of the query/compute engine powering analysis across Amplitude's product suite
- Evolve the compute API and semantic layer that other engineering teams depend on, supporting more generic table structures
- Unify and evolve the core data model, including how non-event data (profile properties, lookup tables) is represented alongside event data
- Improve performance, reliability, and scalability of query planning and execution
- Partner with Session Replay, Experiment, CDP, Query, and frontend teams to understand their needs and shape the compute layer accordingly
- Own projects end-to-end from design through rollout
You should have strong backend or distributed-systems engineering experience, ideally with OLAP databases, query engines, or data infrastructure. SQL expertise, experience with query planning/execution, and a track record of owning ambiguous cross-team projects are essential. Bonus experience includes large-scale event/time-series data systems, semantic layer design, columnar databases, and AI/agent workflow integration.
Example projects include redesigning query representation for faster execution, extending session-based analysis capabilities, improving result caching, extending SQL as an interface for AI agents and third-party tools, bringing non-event data into the core model, and implementing fine-grained data access controls.
