Senior Manager, Data Engineering

Dropbox·Remote - Canada: Select locationsRemotesenior

In short

→Líder técnico de ingeniería de datos que gestiona plataformas de datos críticas para la empresa.
→Se enfoca en calidad, fiabilidad y autoservicio de datos para equipos de producto, marketing y finanzas.
→Destacado: liderar la transformación de trabajo de datos específico en productos reutilizables y escalables.

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What they ask for

✓Líder técnico con experiencia en plataformas de datos a gran escala.
✓Experiencia en gestión de equipos de ingeniería de datos.
✓Enfoque en calidad, observabilidad y fiabilidad de datos.
✓Capacidad para construir plataformas autoservicio para equipos de negocio.
✓Colaboración estrecha con ciencia de datos, BI y producto.
✓Conocimiento profundo en ETL/ELT, orquestación y procesamiento de datos.

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data pipelinesdata productsingestiontransformationorchestrationserving layersself-serve analyticsdata qualitydata lineagefreshness monitoring

Who should you write to at Dropbox?

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Role Description We are seeking a Senior Manager, Data Engineering to lead the team responsible for the reliability, quality, cost, and velocity of Dropbox s core data platform. This is a hands-on engineering leader who owns the pipelines and data products that Product, GTM, Finance, and the CTO organization depend on to make decisions. In this role, you will lead and grow a team of data engineers building and operating our ingestion, transformation, orchestration, and serving layers, as well as the self-serve analytics substrate that lets partner teams answer their own questions without bespoke engineering work. The ideal candidate is a deeply technical, product-minded engineering leader who can hold a high bar on system reliability and data quality while partnering closely with Data Science, Business Intelligence Engineering, Analytics, and Product to turn fragmented, ticket-driven data work into durable, reusable data products. Our Engineering Career Framework is viewable by anyone outside the company and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more here . Responsibilities • Data Quality & Observability: Establish and enforce a rigorous data quality culture: lineage, freshness monitoring, anomaly detection, and outcome-oriented, gaming-resistant quality metrics. • Self-Serve Platform: Lead the engineering of the self-serve analytics substrate, reducing bespoke

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