
Staff Data Engineer, Analytics Data Engineering
Dropbox · United States
- Hybrid
- Full-time
- $230,000 / year
- United States
Job highlights
- Modernize analytics platform and build reusable data models.
- Drive data engineering standards and cross-functional alignment.
- Architect shift-left data governance strategies.
- Collaborate to define reliable data pipelines.
- Integrate AI-native tooling into development lifecycle.
About the role
Staff Data Engineer, Analytics Data Engineering
Dropbox is a Virtual First company. For this role, we are hiring in Zones 2 and 3. Please refer to our Compensation section below to see what neighborhoods fall under each Zone.
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 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.
Requirements
- 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.
Preferred Qualifications
- 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.
Compensation
US Zone 2: $198,900—$269,100 USD
US Zone 3: $176,800—$239,200 USD
The range(s) listed above is the expected annual salary/OTE (On-Target Earnings) for this role, subject to change. Please note, OTE are for sales roles only.
Salary/OTE is just one component of Dropbox’s total rewards package. All regular employees are also eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).
Dropbox takes a number of factors into account when determining individual starting pay, including job and level they are hired into, location/metropolitan area, skillset, and peer compensation. We target most new hire offers between the minimum up to the middle of the range.
Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use. Current US Zone locations are as follows:
US Zone 1: San Francisco metro, New York City metro, or Seattle metro
US Zone 2: California (outside SF metro), Colorado, Connecticut (outside NYC metro), Delaware, Illinois (Chicago metro), Indiana (Chicago metro), Maryland, Massachusetts, Michigan (Chicago metro), New Hampshire, New Jersey (outside NYC metro), New York (outside NYC metro), Oregon, Pennsylvania (D.C. metro), Pennsylvania (outside NYC metro), Texas (Austin metro), Virginia (DC metro), Washington (outside Seattle metro), Washington DC metro, West Virginia (DC metro), Wisconsin (Chicago metro)
US Zone 3: All other US locations
Company Description
Dropbox isn’t just a workplace—it’s a living lab for designing a more enlightened way of working. We’re a global community of bold visionaries and resourceful doers shaping the future of Dropbox and, in turn, the future of work. Our Virtual First model combines the autonomy of a distributed workplace with the power of human connection, creating space for meaningful work and lasting relationships. With a startup mindset and enterprise-level opportunities, we expect Dropbox employees to think critically, stay curious, and use modern tools, including AI, to improve how work gets done. Here, you can be who you are and grow into who you’re meant to be. You own your impact, helping make work more intuitive, joyful, and human for yourself and hundreds of millions of people worldwide. If you’re ready to push boundaries and challenge yourself, Dropbox is ready for you.
Team Description
The Dropbox Engineering Team develops the technology, platforms, and products that create more enlightened ways of working for hundreds of millions of people. Customers rely on Dropbox to manage, share, and collaborate on content seamlessly—our engineering makes that easier and more intuitive than ever before.Our platform features a robust systems software layer that stores and processes exabytes of data, and a suite of growing services that enhance core products like our sharing and sync engine. We’re also driving innovation with new offerings such as Dash, our AI-powered knowledge management engine. Our infrastructure spans high-performance servers and cutting-edge components across multiple data centers worldwide, ensuring reliability, speed, and scalability at a global scale. We think like a startup but build for an enterprise, exploring new possibilities that transform how people work. If you're excited about turning complex technical challenges into intuitive solutions at scale, join our Engineering team.
Virtual First
Dropbox’s Virtual First way of working is designed to help people do their best work with flexibility, autonomy, and connection. Day to day, teams work remotely with nonlinear schedules and core collaboration hours that support deep focus and individual working styles. We prioritize asynchronous communication to improve clarity, respect deep work time, and reduce unnecessary meetings. While remote work is the primary experience for our employees, we also prioritize intentional, in-person connection. We bring teams together through regular team gatherings, on-demand workspaces, and Dropbox Neighborhood events in order to strengthen team cohesion, foster creativity, and enhance momentum. Virtual First is built to provide the same access to opportunity, growth, and impact for everyone, regardless of location.
This role requires travel to offsites and various other team gatherings (approximately 5-10% of the year or 2-3 days per quarter). We provide advance notice when possible and encourage candidates to discuss any accommodation needs during the interview process.
AI Fluency
About
At Dropbox, AI fluency is a core part of how we work and grow. It’s not about being an AI expert, it’s about how thoughtfully and effectively you use AI to improve your work and support others. We look for four key behaviors in our candidates:
- AI Ownership: You use AI responsibly—protecting data, applying sound judgment, and taking accountability for the quality and accuracy of your work.
- AI Experimentation: You actively explore new AI capabilities and apply them to improve workflows, staying within approved tools and practices.
- AI Leverage: You use AI as a multiplier, enhancing your thinking, increasing efficiency, and improving the impact of your work and your team’s work.
- AI Learning: You stay current on emerging tools and trends, continuously build your skills, and share what you learn with others.
Together, these behaviors build an AI-fluent workforce where technology amplifies human judgment, creativity, and impact.
Dropbox supports responsible use of AI for preparation, but misrepresentation of skills or experience is not permitted. See our AI Principles.
Dropbox is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work.
Key skills/competency
- Staff Data Engineer
- Analytics Data Engineering
- Data Modeling
- Orchestration Tools
- Data Governance
- SQL
- Python
- Data Pipelines
- Databricks
- AI-native tooling
Skills & topics
- Staff Data Engineer
- Data Engineering
- Analytics
- Data Modeling
- SQL
- Python
- Airflow
- dbt
- Data Governance
- Databricks
How to get hired
- Tailor your resume: Highlight your 12+ years of data engineering experience, leadership, SQL, and Python skills.
- Showcase leadership: Emphasize experience driving cross-team alignment and establishing data standards.
- Quantify achievements: Provide examples of successful data model designs and pipeline modernizations.
- Demonstrate tool proficiency: Detail your experience with Airflow, dbt, and modern lakehouse architectures.
- Prepare for behavioral questions: Be ready to discuss your approach to data governance and influencing without authority.
Technical preparation
Behavioral questions
Frequently asked questions
- What is the salary range for the Staff Data Engineer role at Dropbox in US Zone 2?
- For the Staff Data Engineer position at Dropbox in US Zone 2, the expected annual salary range is $198,900 to $269,100 USD. This is part of Dropbox's total rewards package, which also includes corporate bonuses and stock options.
- What is the salary range for the Staff Data Engineer role at Dropbox in US Zone 3?
- The expected annual salary for the Staff Data Engineer role at Dropbox in US Zone 3 ranges from $176,800 to $239,200 USD. This compensation is in addition to other benefits like corporate bonuses and Restricted Stock Units (RSUs).
- What does 'Virtual First' mean at Dropbox for this Staff Data Engineer position?
- Dropbox's 'Virtual First' model means the role is primarily remote, offering flexibility and autonomy. While remote work is the norm, there will be intentional in-person gatherings for teams, requiring about 5-10% travel per year.
- What are the key technical skills required for the Staff Data Engineer role at Dropbox?
- Key technical skills for this Staff Data Engineer role include 12+ years of SQL (including Spark SQL), 8+ years of Python for data pipelines, deep expertise in dimensional data modeling, schema design, and experience with orchestration tools like Airflow and dbt.
- Does Dropbox require on-call rotations for the Staff Data Engineer role?
- Yes, many teams at Dropbox, including potentially this one, have on-call rotations. Participation in these rotations, which may include non-core business hours, is expected as part of the role. Candidates are encouraged to inquire for specific details.
- What is Dropbox's approach to AI for the Staff Data Engineer position?
- Dropbox encourages AI fluency, focusing on responsible AI ownership, experimentation, leverage, and learning. Candidates are expected to thoughtfully and effectively use AI to improve their work, with a strong emphasis on data protection and sound judgment.
- What is the educational requirement for the Staff Data Engineer role at Dropbox?
- A BS degree in Computer Science or a related technical field is preferred, but equivalent technical experience is also accepted for the Staff Data Engineer role at Dropbox.
- How does Dropbox determine the starting pay for a Staff Data Engineer?
- Dropbox determines starting pay based on several factors, including the job level, candidate's location/metropolitan area, specific skill set, and peer compensation data. They typically aim to offer new hires within the minimum to the middle of the stated salary range.
- What are the preferred qualifications for the Staff Data Engineer role at Dropbox?
- Preferred qualifications include experience with Databricks (Unity Catalog, Delta Lake), modern lakehouse architectures, leading platform modernization efforts, familiarity with data governance/observability tools (Atlan, Monte Carlo), and experience with metrics/semantic layers like dbt MetricFlow.
- What is the significance of 'data governance' in this Staff Data Engineer role at Dropbox?
- Data governance is a critical aspect, involving architecting a shift-left strategy, establishing data contracts, SLOs, and quality gates with upstream producers to ensure data reliability and catch issues early in the development lifecycle.