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Infrastructure and data

Data Platform Engineer

This role owns the data layer that the product depends on: ingestion, storage, transformation, and query performance. You will design systems that handle high-volume AI output reliably and give the product the data quality it needs to report with confidence.

Candidaturas pronto

Resumen del rol

Build and maintain the data infrastructure that makes AI visibility analysis reliable, fast, and scalable as prompt volume and reporting complexity grow.

Por qué existe este rol

Data volume is increasing faster than the current infrastructure was designed for. We need someone to build a platform that can grow with the product without becoming a constant maintenance burden.

Primeros 90 días

Map the current data flow end to end and identify the top three reliability or performance gaps.

Por qué existe este rol

Data volume is increasing faster than the current infrastructure was designed for. We need someone to build a platform that can grow with the product without becoming a constant maintenance burden.

En qué trabajarás

  • Design and operate data pipelines from AI prompt execution through to query-ready reporting tables.
  • Own storage, schema design, and query optimization for high-volume, time-series AI output data.
  • Build internal tooling that helps the research and product teams explore and validate data quality.
  • Establish data observability practices so problems are caught before they reach the product.

Cómo se ve un gran encaje

  • Strong experience designing data pipelines and schemas for analytical workloads.
  • Comfort with time-series data, partitioning strategies, and query performance at volume.
  • Experience building and operating pipelines that handle partial failures, late data, and schema evolution.
  • A product mindset: you understand that bad data leads to bad product decisions.

Qué te entusiasmará aquí

  • Building the data foundation for a product category that does not have an established playbook yet.
  • Owning the full data platform, not just one pipeline.
  • Working on infrastructure where quality directly determines whether the product can be trusted.

Primeros 90 días

  1. 01Map the current data flow end to end and identify the top three reliability or performance gaps.
  2. 02Ship at least one pipeline improvement that reduces latency or error rate on a core data path.
  3. 03Establish basic data observability so the team has visibility into pipeline health.

Proceso de hiring

El proceso es intencionalmente corto, directo y anclado en el trabajo real.

  1. 1

    Solicitud

    Envíanos tu trayectoria, trabajo relevante y por qué este rol tiene sentido para ti.

  2. 2

    Conversación base

    Una conversación centrada en tu trabajo, tu criterio y el rol.

  3. 3

    Profundización específica del rol

    Una conversación o ejercicio que se parezca al trabajo real más que a un bucle genérico.

  4. 4

    Conversación con el fundador

    Una charla final sobre estándares, ambición y cómo sería el éxito aquí.

  5. 5

    Decisión

    Cerramos el proceso con claridad y nos movemos rápido cuando hay convicción.

¿Necesitas contexto antes de aplicar? [email protected]

Data Platform Engineer

Este rol ya es visible en la web. Las candidaturas se activan en cuanto el puesto correspondiente en Dover esté activo.

Las candidaturas permanecen cerradas hasta que el puesto correspondiente en Dover se active. Mientras tanto puedes escribir a [email protected].