Staff Data Engineer Analytics Data Engineering

Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering (ADE) team within Data Science & AI Platform. You will be responsible for solving cross-cutting data challenges that span multiple lines of business while driving standardization in how we build deploy and govern analytics pipelines across Dropbox.

This is not a maintenance role. We are modernizing our analytics platform upgrading orchestration infrastructure building shared and reusable data models with conformed dimensions establishing a certified metrics framework and laying the foundation for AI-native data development. You will partner closely with Data Science Data Infrastructure Product Engineering and Business Intelligence teams to make this happen.

You will play a crucial role in establishing analytics engineering standards designing scalable data models and driving cross-functional alignment on data governance. You will get substantial exposure to senior leadership shape the technical direction of analytics infrastructure at Dropbox and directly influence how data powers product and business decisions.

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.

• 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

Many teams at Dropbox run Services with on-call rotations which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

• 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

• Experience with Databricks (Unity Catalog Delta Lake) and modern lakehouse architectures
• Experience leading orchestration or platform modernization efforts at scale
• Familiarity with data governance and observability tools such as Atlan Monte Carlo Great Expectations or similar
• Experience building or contributing to a metrics/semantic layer (dbt MetricFlow Databricks Metric Views or equivalent)
• Track record of establishing data engineering standards and best practices in a federated analytics organization

What We Do

We're a global community of bold visionaries and resourceful doers who are shaping the future of Dropbox—and with it the future of work. Our Virtual First model combines the flexibility of a distributed workplace with the power of human connection making space for both meaningful work and meaningful relationships. With our start-up mindset and enterprise-level opportunities you can be who you are and grow into who you’re meant to be. Here you can own your impact to make work more intuitive joyful and human—for you as a Dropboxer and for hundreds of millions of people worldwide. If you're ready to push boundaries—and yourself—Dropbox is ready for you.

Why Work With Us

We believe people do their best work when empowered with autonomy and harmony and we understand there’s no substitute for human connection. Our Virtual First model combines the flexibility of remote work with the power of in-person collaboration to create the best of both worlds: a distributed workplace anchored in community.

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