Analytics Platform Engineer

Details

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