Staff Data Engineer, Analytics Data Engineering

🕒 Fevereiro 18

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $176.800 - $239.200 / ano

⏰ Tempo Integral

🔴 Especialista

🚰 Engenheiro de Dados

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Dropbox

SiteLinkedInTodas as Vagas

1001 - 5000 funcionários

Fundada em 2007

🏢 Corporativo

⚡ Produtividade

Cloud Storage • Enterprise • Productivity

O Dropbox é um serviço baseado na nuvem que fornece ferramentas para armazenar, compartilhar e acessar arquivos em vários dispositivos. Ele oferece funcionalidades como compartilhamento de documentos, revisão de vídeos, backups automáticos e agendamento impulsionado por IA. O Dropbox também fornece soluções para diferentes setores como equipes, vendas, marketing e educação, e indústrias incluindo construção, mídia, tecnologia e manufatura. Com foco em segurança, o Dropbox garante que os arquivos sejam criptografados e protegidos contra adulteração. Ele oferece integrações com várias ferramentas de produtividade e é confiável por grandes empresas para uma gestão de arquivos e colaboração eficiente.

Descrição

• Lead the design and implementation of shared, reusable data models, defining shared fact tables, conformed dimensions, and a semantic/metrics layer that serves as the single source of truth across analytics functions • Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards • Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access • Architect and implement a shift-left data governance strategy, working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production • Collaborate with Data Science leads and Product Management to translate metric definitions into reliable, certified data pipelines that power executive dashboards, WBR reporting, and growth measurement • Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable • Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development

🎯 Requisitos

• BS degree in Computer Science or related technical field, or equivalent technical experience • 12+ years of experience in data engineering or analytics engineering with increasing scope and technical leadership • 12+ years of SQL experience, including complex analytical queries, window functions, and performance optimization at scale (Spark SQL) • 8+ years of Python development experience, including building and maintaining production data pipelines • Deep expertise in dimensional data modeling, schema design, and scalable data architecture, with hands-on experience building shared data models across multiple business domains • Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns • Demonstrated ability to drive cross-team technical alignment, establishing standards, influencing without authority, and working across Data Engineering, Data Science, Data Infrastructure, and Product Engineering boundaries

🏖️ Benefícios

• US Zone 2: $198,900 - $269,100 USD • US Zone 3: $176,800 - $239,200 USD