Senior Data Engineer

• BS or MS degree in Computer Science, Engineering, or a related technical field
• Strong SQL skills
• 5+ years of experience working with event instrumentation, data pipelines, and data warehouses, preferably acting as a data architect in a previous role
• Proficiency with systems design and data modeling
• Fluency with workflow management tools, like Airflow or dbt
• Experience with modern data warehouses, like Snowflake or BigQuery
• Expertise breaking down complex problems, documenting solutions, and sequencing work to make iterative improvements
• Familiarity with marketing data tech stack
• Familiarity with data visualization tools such as Mode, Tableau, and Looker
• Familiarity with programming skills, preferably in Python
• Familiarity with software design principles, including test-driven development

Data Platform is on a mission to democratize learning by building systems that enable company-wide analytics and experimentation. By implementing sufficient instrumentation, designing intuitive data models, and building batch/streaming pipelines, we will allow for deep and scalable investigation and optimization of the business. By developing self-serve tools, we will empower executives, PMs & engineering leadership to understand company performance at a glance and uncover insights to support decision making. Finally, by building capabilities such as forecasting, alerting, and experimentation, we will enable more, better, and faster decisions.

• Drive direct business impact with executive-level visibility
• Design technical architecture and implement components from the ground up as we transition to event-based analytics
• Work on the unique challenge of joining a variety of online and offline data sets, not just big data
• Learn and grow Data Science and Data Analytics skills (we sit in the same org!)
• Opportunity to grow into a Tech Lead/Manager, and mentor junior team members as we quickly grow the team
• Partner with infrastructure and product engineers to instrument our backend services and end-to-end user journeys to create visibility for the rest of the business
• Design, develop and monitor scalable and cost-efficient data pipelines and build out new integrations with third-party tools
• Work with data analysts and data scientists to design our data models as inputs to metrics and machine learning models
• Establish the best practices for data engineering
• Assess build vs buy tradeoffs for components in our company-wide analytics platform, which will inform decision-making for executives, PMs and Ops, etc.