• 5+ years of experience in a data-professional capacity such as Data Analyst, Data Scientist, and/or Analytics Engineer
• Expert SQL knowledge and experience developing data models using DBT
• Fundamental understanding of D2C businesses and unit economics
• Ability to collect required data from internal and external systems, design data storage structures, and build automated data pipelines that are reliable and scalable in a fast-growing data ecosystem. Preferred experience with Fivetran, Airflow, and/or Airbyte
• A strong understanding of data modeling principles and modern data platforms to build data model architecture, data ETL processes, reporting, and analytics solutions. Preferred experience with Snowflake, DBT, Looker, HighTouch, and Segment
• The ability to push the boundaries of analytical insights with modern machine learning and data science stacks (including Python)
• Strong individual contributor who can operate autonomously throughout an organization across all levels and manage multiple projects across stakeholders in a fast-paced environment

Desirable

• As a Senior Data Analyst, you will be a key member of Public’s data analytics and engineering team and will report directly to the Head of Strategic Finance
• You will build systems that process data efficiently and scale with our business, and then model that data to enable analytics and insights across the business
• You will collaborate cross-functionally to help execute a variety of complex data projects in alignment with our business goals and product roadmap
• Develop an in-depth understanding of our business fundamentals and success metrics in order to build data solutions that capture top-line initiatives and inform decision-making
• Partner closely with our engineering and product pods to provide data and insights on our most important brokerage features
• Build and manage advanced reporting, dashboards, data models, and tools to support cross-functional teams and initiatives, and enable teams to self-service where possible, while being the primary point of contact for ad hoc data requests
• Extract, manipulate, cleanse, and synthesize data from a variety of sources through ETL technologies
• Identity, manage, and implement data-driven recommendations for product and lifecycle marketing through alerts, automated reverse ETL pipelines, A/B testing, and machine learning applications
• Be a thought leader in refining the ways we are developing, testing, deploying, organizing and documenting our data infrastructure, data transformation models, and BI tools for self-service reporting