Staff Data Engineer, Commerce Data

Role Description

Dropbox seeks a highly skilled and motivated Staff Data Engineer to join our Commerce Platform team. You will be responsible for building next-generation commerce data pipelines that support crucial business decisions across the organization. The ideal candidate will have a strong culture of innovation and accountability, and expertise in developing data health metrics that integrate with data governance, observability, and quality management tools. This role includes maintaining existing pipelines, and constructing new infrastructure to replace outdated systems.

As a Staff Data Engineer at Dropbox, you will act as a leader and senior member of the team helping them build very large, scalable platforms using cutting edge 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!

Responsibilities

• You will help define company data assets (data models) using Spark, Spark SQL and Databricks SQL jobs to populate data models
• You will help define and design data integrations, data quality, and governance frameworks and design and evaluate open source/vendor tools to improve development velocity
• You will help define data engineer best practices.
• You will work closely with Dropbox business units and engineering teams to develop a data strategy and data architecture to support Dropbox’s long term business goals

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 involving coding (e.g., physics or mathematics), or equivalent technical experience
• 10+ years of Python development experience
• 10+ years of SQL experience (Spark and Databricks-specific SQL is a plus)
• 10+ years of experience with schema design, dimensional data modeling, and scalable data architecture
• Demonstrable track record managing, communicating, and collaborating with internal clients on data platform plans and capabilities
• Experience designing, building and maintaining data processing systems
• Experience working with data at significant scale and optimizing queries and pipelines

Preferred Qualifications

• 7+ years of Spark SQL and non-SQL Spark development experience
• 7+ years of Snowflake development experience
• 7+ years of development of Airflow data pipelines
• 5+ years of experience with Hive Map/Reduce
• 7+ years of Databricks platform experience including Spark and Databricks development

Compensation