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Salary: CAD 101,200 - 136,900 / annual
As a Data Engineer on Dropbox's Analytics Data Engineering team, you will build and operate the pipelines and data models that power the company's understanding of its products and business. You will own well-scoped pipelines end-to-end—from design and build through testing, deployment, monitoring, and iteration—with senior engineers available for guidance on harder architectural decisions.
Your work directly feeds the datamarts and KPIs used by data scientists, analysts, product managers, and company leadership, so the quality and reliability of what you build is visible quickly. This is a build-oriented team working on a modern stack, not a maintenance role, and a strong place to develop into an engineer who can own a full data domain.
Key responsibilities include:
- 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
Dropbox publishes an Engineering Career Framework viewable by anyone outside the company, which describes expectations at each career level.
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)
