Role Description
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.
Responsibilities
- 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
- pythongoaidataanalyticsproductdesign
