Staff Data Engineer

<h2>Role Description</h2> <p>Dropbox is looking for a Staff Data Engineer to join our Analytics Data Engineering <span class=" h-lparen">(ADE)</span> team within Data Science &amp; 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.</p> <p>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.</p> <p>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.</p> <div> <p><span class=" author-d-iz88z86z86za0dz67zz78zz78zz74zz68zjz80zz71z9iz90z95lz89zy6z71zz79zz84zz68zyz69zupz72zz79zcz69zz76zkz79zp1z66ztz67zxz71zz89zz86zz71z">Our Engineering Career Framework is </span><span class="attrlink url author-d-iz88z86z86za0dz67zz78zz78zz74zz68zjz80zz71z9iz90z95lz89zy6z71zz79zz84zz68zyz69zupz72zz79zcz69zz76zkz79zp1z66ztz67zxz71zz89zz86zz71z"><a class="attrlink" href="https://dropbox.github.io/dbx-career-framework/" target="_blank" data-target-href="https://dropbox.github.io/dbx-career-framework/"><u>viewable by anyone outside the company</u></a></span><span class=" author-d-iz88z86z86za0dz67zz78zz78zz74zz68zjz80zz71z9iz90z95lz89zy6z71zz79zz84zz68zyz69zupz72zz79zcz69zz76zkz79zp1z66ztz67zxz71zz89zz86zz71z"> and describes what’s expected for our engineers at each of our career levels. Check out our blog post on this topic and more </span><span class="attrlink url author-d-iz88z86z86za0dz67zz78zz78zz74zz68zjz80zz71z9iz90z95lz89zy6z71zz79zz84zz68zyz69zupz72zz79zcz69zz76zkz79zp1z66ztz67zxz71zz89zz86zz71z"><a class="attrlink" href="https://dropbox.tech/culture/sharing-our-engineering-career-framework-with-the-world" target="_blank" data-target-href="https://dropbox.tech/culture/sharing-our-engineering-career-framework-with-the-world">here</a></span><span class=" author-d-iz88z86z86za0dz67zz78zz78zz74zz68zjz80zz71z9iz90z95lz89zy6z71zz79zz84zz68zyz69zupz72zz79zcz69zz76zkz79zp1z66ztz67zxz71zz89zz86zz71z">.</span></p> </div> <h2>Responsibilities</h2> <ul> <li>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</li> <li>Drive standardization of data engineering practices across ADE and functional analytics teams, including pipeline patterns, CI/CD workflows, naming conventions, and data modeling standards</li> <li>Partner with Data Infrastructure to modernize orchestration, improve pipeline decomposition, and establish secure dev/test environments with production data access</li> <li>Architect and implement a shift-left data governance strategy, &nbsp;working with upstream data producers to establish data contracts, SLOs, and code-enforced quality gates that catch issues before production</li> <li>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</li> <li>Reduce operational burden by improving pipeline granularity, observability, and failure recovery, establishing runbooks and alerting standards that make on-call sustainable</li> <li>Evaluate and integrate AI-native tooling into the data development lifecycle, enabling conversational data exploration with guardrails and AI-assisted pipeline development</li> </ul> <p><span class="thread-348589118974529206372994 attrcomment attrcommentfirst thread-348589118974529206372994-first author-d-iz88z86z86za0dz67zz78zz78zz74zz68zjz80zz71z9iz90z95lz89zy6z71zz79zz84zz68zyz69zupz72zz79zcz69zz76zkz79zp1z66ztz67zxz71zz89zz86zz71z">On-call work may be necessary occasionally to help address bugs, outages, or other operational issues, with the goal of maintaining a stable and high-quality experience for our customers.</span></p> <h2>Requirements</h2> <ul> <li>BS degree in Computer Science or related technical field, or equivalent technical experience</li> <li>12+ years of experience in <span class="highlight" data-highlight-color="#D8C3FF">data engineering or analytics engineering</span> with increasing scope and technical leadership</li> <li>12+ years of <span class="highlight" data-highlight-color="#D8C3FF">SQL</span> experience, including <span class="highlight" data-highlight-color="#D8C3FF">complex analytical queries, window functions, and performance optimization at scale</span> <span class="highlight h-lparen" data-highlight-color="#D8C3FF">(Spark</span><span class="highlight" data-highlight-color="#D8C3FF"> SQL)</span></li> <li>8+ years of <span class="highlight" data-highlight-color="#D8C3FF">Python</span> development experience, including building and maintaining production data pipelines</li> <li><span class="thread-953794937530940541624363 attrcomment attrcommentfirst thread-953794937530940541624363-first"><span class="comment-extra-inner-span">Deep expertise in </span></span><span class="highlight thread-953794937530940541624363 attrcomment" data-highlight-color="#D8C3FF"><span class="comment-extra-inner-span">dimensional data modeling, schema design, and scalable data architecture,</span></span><span class="thread-953794937530940541624363 attrcomment"><span class="comment-extra-inner-span"> with hands-on experience building shared data models across multiple business domains</span></span></li> <li>Strong experience with<span class="highlight" data-highlight-color="#D8C3FF"> orchestration tools</span> <span class=" h-lparen">(Airflow</span> strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns</li> <li>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</li> </ul> <h2>Preferred Qualifications</h2> <ul> <li>Experience with<span class="highlight" data-highlight-color="#F7CC62"> Databricks</span> <span class=" h-lparen">(Unity</span> Catalog, Delta Lake) and modern lakehouse architectures</li> <li>Experience leading orchestration or platform modernization efforts at scale</li> <li><span class="highlight" data-highlight-color="#F7CC62">Familiarity with data governance and observability tools such as Atlan, Monte Carlo, Great Expectations, or similar</span></li> <li>Experience building or contributing to a metrics/semantic layer <span class=" h-lparen">(dbt</span> MetricFlow, Databricks Metric Views, or equivalent)</li> <li><span class="highlight" data-highlight-color="#F7CC62">Track record of establishing data engineering standards and best practices in a federated analytics organization</span></li> </ul> <p>&nbsp;</p>