Role DescriptionIn this role you will build large, scalable analytics pipelines using modern data technologies. This is not a “maintain existing platform” or “make minor tweaks to current code base” kind of role. We are effectively building from the ground up and plan to leverage the most recent Big Data technologies. If you enjoy building new things without being constrained by technical debt, this is the job for you! 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 - 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 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 - 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 Preferred Qualifications - 7+ years of SQL experience - 7+ years of experience with schema design, dimensional data modeling, and medallion architectures - Experience with Airflow or other similar orchestration frameworks - Experience building data quality monitoring using MonteCarlo or similar tools Compensation US Zone 1 This role is not available in Zone 1 US Zone 2 $149,200—$201,800 USD US Zone 3 $132,600—$179,400 USD

• Architecture, development and management of the data platform to support efficient data ingestion, transformation, quality checks, monitoring and accessibility. • Work closely with cross-functional teams to capture data requirements. • Contribute to shaping and implementing the technical vision and roadmap for the data platform. • Technologies you will work with include: Google Cloud Platform (Cloud Run, BigQuery, Pub/Sub, Dataform, etc.), SQLMesh, Cursor, Terraform / Terramate, GitHub Actions, Python and SQL, Looker.

• Design and develop web and mobile platforms • Collaborate with the South American team and clients • Manage and optimize data processes and workflows • Ensure high standards of quality and performance in solutions

• Assemble and manage large, complex datasets that meet both non-functional and functional business requirements. • Identify, design, and implement internal process improvements to enhance scalability, optimize data delivery, and automate manual processes. • Build and maintain optimal data pipeline architecture for efficient extraction, transformation, and loading of data from various sources. • Provide technical expertise and support for data-related issues. • Partner with data and analytics experts to enhance functionality and performance of data systems. • Design and deploy frameworks and microservices to serve data assets to data consumers. • Performs root cause analysis on data and processes to identify opportunities for improvement. • Act as a trusted advisor and partner to business leads, understanding their needs, interpreting data drivers, and aligning data strategies with business goals. • Evaluate customer requirements and contribute to the development of structural necessities within the data architecture. • Ensure database implementation procedures comply with relevant regulations. • Organize data within cloud storage and implement appropriate security measures. • Collaborate cross-functionally with multiple teams within the organization. • Works independently and collaboratively in a team environment.