companyDropbox, Inc. logo

Staff Data Engineer - Analytics Data Engineering

Dropbox, Inc.Remote - US: Select locations
Remote Full-time $176.8K/yr - $269.1K/yr

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Experience Level

Mid to Senior

Qualifications

QualificationsProven experience in data engineering and analytics. Strong understanding of analytics frameworks and data governance. Expertise in designing scalable data models and constructing complex analytics pipelines. Experience collaborating with cross-functional teams. Excellent communication skills to convey technical concepts to non-technical stakeholders.

About the job

Dropbox is seeking a talented Staff Data Engineer to join our Analytics Data Engineering (ADE) team within the Data Science & AI Platform. In this role, you will tackle complex data challenges across various business lines while leading the initiative to standardize how we construct, deploy, and manage analytics pipelines at Dropbox.

This is not a maintenance position. You will be at the forefront of modernizing our analytics platform, enhancing our orchestration infrastructure, creating shared and reusable data models with conformed dimensions, establishing a certified metrics framework, and setting the groundwork for AI-driven data development. Collaborating closely with teams in Data Science, Data Infrastructure, Product Engineering, and Business Intelligence will be essential to your success.

Your contributions will be pivotal in establishing analytics engineering standards, designing scalable data models, and ensuring cross-functional alignment on data governance. This role provides substantial exposure to senior leadership, allowing you to shape the technical direction of analytics infrastructure at Dropbox and significantly influence how data drives product and business decisions.

About Dropbox, Inc.

Dropbox, a leading provider of cloud storage and collaboration tools, is committed to simplifying how people work together. Our innovative solutions empower teams to be more productive, creative, and efficient, all while prioritizing data security and user experience.

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