- 雇用形態
- Full Time
- 勤務形態
- Remote
- 給与
- 記載なし
この仕事について
仕事内容は掲載元の言語で表示しています。最新の条件は企業の募集ページでご確認ください。
Open Role
Data Engineer
- Remote - Canada: Select locations
- Remote
- Engineering
- Full Time
Dropbox is a Virtual First company. For this role, we are currently only authorized to hire candidates from the following provinces: Alberta, British Columbia, Ontario, and Saskatchewan.
Role Description
As a Data Engineer on Analytics Data Engineering, you will build and operate the pipelines and data models the rest of Dropbox relies on to understand its products and its business. You will own well-scoped pipelines end to end — design, build, test, ship, monitor — with senior engineers alongside you for the harder architectural calls.
Your work feeds the datamarts and KPIs used by data science, product, and company leadership, so the quality of what you build is visible quickly. This is a build-oriented team on a modern stack rather than a maintenance role, and a strong place to develop into an engineer who can own a full data domain.
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
- Build and maintain Spark and SparkSQL jobs that populate company data models
- Own well-scoped pipelines end to end, from requirements through deployment, monitoring, and iteration
- Contribute to data quality frameworks, testing, and data lineage instrumentation
- Partner with data scientists, analysts, product managers, and engineers to turn data needs into durable models
- Extend datamarts and data models supporting recurring reporting and analysis across products
- Improve the reliability and cost efficiency of existing pipelines, dashboards, and frameworks
- Participate in a business-hours on-call rotation and help improve runbooks and alerting
- 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
- 2+ years of development experience in Spark, Python, Java, C++, or Scala
- 2+ years of SQL experience, including query performance tuning
- 2+ years of experience with schema design and dimensional data modeling
- Experience building and maintaining production data pipelines that others depend on
- Working exposure to a cloud data lake or lakehouse platform, Databricks preferred
- Clear written and verbal communication with non-engineering partners, and a track record of asking for help and feedback early
- BS in Computer Science or a related technical field involving coding (e.g. physics or mathematics), or equivalent technical experience
Preferred Qualifications
- 4+ years of SQL experience
- Experience with medallion architectures and incremental data modeling patterns
- Experience with Airflow or a similar orchestration framework
- Exposure to data quality monitoring using Monte Carlo or similar tools
- Exposure to streaming architectures (Kafka, Kinesis, Structured Streaming)
Durable Skills
- AI fluency means using these tools to amplify human judgment, not replace it.
- We believe people with these skills will thrive as work and technology continue to evolve:
- Awareness: Understand yourself and others.
- Judgment: Evaluate information and make decisions in complex situations.
- Adaptability: Learn, adjust, and stay effective through change.
- Connection: Communicate, collaborate, and build trust.
- To learn more about why these skills matter and what the data shows about thriving through change, read this blog post from our Chief People Officer, Melanie Rosenwasser.
Compensation
Canada Pay Range
$101,200—$136,900 CAD
The range listed above is the expected annual salary/OTE (On-Target Earnings) for this role, subject to change.
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).
Read more about our benefits here.
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
AI fluency is a core part of how we work and grow. It’s not about being an expert—it’s about using these tools thoughtfully and effectively to improve your work and support others.
We look for four key behaviors in candidates:
- Ownership: You use AI responsibly by protecting data, applying sound judgment, and taking accountability for the quality and accuracy of your work.
- Experimentation: You explore new AI capabilities and apply them to improve workflows within approved tools and practices.
- Leverage: You use AI to enhance thinking, improve efficiency, and increase your impact and your team’s.
- Learning: You stay current on emerging AI tools and trends, continuously build your skills, and share what you learn with others.
Together, these behaviors help build a 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. To learn more, see our approach to AI in hiring .
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.
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主な業務内容
- Build and maintain Spark and SparkSQL jobs that populate company data models
- Own well-scoped pipelines end to end, from requirements through deployment, monitoring, and iteration
- Contribute to data quality frameworks, testing, and data lineage instrumentation
- Partner with data scientists, analysts, product managers, and engineers to turn data needs into durable models
- Extend datamarts and data models supporting recurring reporting and analysis across products
- Improve the reliability and cost efficiency of existing pipelines, dashboards, and frameworks
- Participate in a business-hours on-call rotation and help improve runbooks and alerting
- 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.
応募要件
- 2+ years of development experience in Spark, Python, Java, C++, or Scala
- 2+ years of SQL experience, including query performance tuning
- 2+ years of experience with schema design and dimensional data modeling
- Experience building and maintaining production data pipelines that others depend on
- Working exposure to a cloud data lake or lakehouse platform, Databricks preferred
- Clear written and verbal communication with non-engineering partners, and a track record of asking for help and feedback early
- BS in Computer Science or a related technical field involving coding (e.g. physics or mathematics), or equivalent technical experience
- Preferred Qualifications: 4+ years of SQL experience
- Preferred Qualifications: Experience with medallion architectures and incremental data modeling patterns
- Preferred Qualifications: Experience with Airflow or a similar orchestration framework
- Preferred Qualifications: Exposure to data quality monitoring using Monte Carlo or similar tools
- Preferred Qualifications: Exposure to streaming architectures (Kafka, Kinesis, Structured Streaming)