Data Engineer specializing in building scalable analytics data pipelines at Dropbox. Focusing on leveraging the latest Big Data technologies without technical debt.
Responsibilities
Help define company data assets (data model), Spark, SparkSQL jobs to populate data models
Help define and design data integrations, data quality frameworks and design and evaluate open source/vendor tools for data lineage
Work closely with Dropbox business units and engineering teams to develop strategy for long term Data Platform architecture to be efficient, reliable and scalable
Conceptualize and own the data architecture for multiple large-scale projects, while evaluating design and operational cost-benefit tradeoffs within systems
Collaborate with engineers, product managers, and data scientists to understand data needs, representing key data insights in a meaningful way
Design, build, and launch collections of sophisticated data models and visualizations that support multiple use cases across different products or domains
Optimize pipelines, dashboards, frameworks, and systems to facilitate easier development of data artifacts
Requirements
5+ years of Spark, Python, Java, C++, or Scala development experience
5+ years of SQL experience
5+ years of experience with schema design, dimensional data modeling, and medallion architectures
Experience with the Databricks platform and data lake architectures for large-scale data processing and analytics
Excellent product strategic thinking and communications to influence product and cross-functional teams by identifying the data opportunities to drive impact
BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics), or equivalent technical experience
Experience designing, building and maintaining data processing systems
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