Resumen del rol

Data Platform Engineer

Requisitos y responsabilidades

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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.
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