Responsibilities

Own, operate, and improve Cursor’s Databricks and lakehouse infrastructure as the data team size and data volume scales
Build and optimize ingestion systems for first-party product data and 3rd-party business systems
Ensure observability, alerting, and operational standards across all data infrastructure layers
Evaluate and roll out data tooling where it solves real stakeholder needs, including BI platforms, catalogs, ingestion tools, and reverse ETL systems
Partner with technical and non-technical partners to understand recurring data problems and turn them into scalable platform solutions

Example Projects

Own and optimize the raw data layer: Improve the performance, reliability, and cost profile of TB-scale first-party data ingestion so downstream analysis, experimentation, and ETL are faster and more trustworthy
Scale orchestration for a growing data team: Make Dagster and related orchestration infrastructure reliable, observable, and ergonomic for a large base of data scientists, analytics engineers, and adjacent technical users
Expand and secure agentic data capabilities: Enable new entrypoints and capabilities for agents to do data work, all while keeping security and privacy requirements high

4+ years of full-time data platform engineering experience
Built up modern data stacks at a low level, not just written jobs on top of it
Scaled performant ingestion of billions of data per day
Go-to person for data pipeline orchestration infrastructure used by large user bases; Dagster experience is a strong plus
Want to build foundational systems at a company where data-savvy users will immediately push them to their limits