In this role, you will be joining a team of data scientists and engineers. You'll help build and maintain the semantic layer of our data pipeline, ensuring clean, consistent, and reusable data models. Day-to-day activities range from developing and testing data models, editing LookML, managing a data catalog, automating data analysis workflows, and working closely with stakeholders to understand and support their data needs.

What you'll learn

An important part of our culture is continuing education and the sharing of ideas. We offer:

• A large network of investors and advisors for you to access that will help your team succeed
• Mentorship from executives with decades of experience in adtech and media
• Regular internal knowledge-sharing sessions
• Education budget to accelerate your team’s development

Specifically, in this role, you will learn:

• Gain a deep understanding of attention metrics and media quality measurement
• How to build and maintain modular, scalable data models using tools like dbt and Looker (LookML)
• Best practices for working millions of data points
• How to collaborate effectively across teams to meet stakeholder needs

Core Responsibilities

• Assist in building, testing, and maintaining transformational data models (dbt, Redshift)
• Help create and manage a clean, reliable reporting layer in Looker using LookML
• Work cross functionally with emphasized support to the Analytics Team
• Help identify and automate manual data analysis processes (python, dbt)
• Contribute to maintaining a well-organized data catalog with accurate, accessible metadata for both technical and non-technical audiences
• Ensure metric consistency across dashboards and data tools
• Collaborate with analysts and PMs to document key metrics and definitions
• Monitor adoption and identify opportunities for improved data usability

What you'll bring

• SQL Proficiency - Strong ability to write, optimize, and debug SQL queries. You also understand data modeling and warehouse best practices, and you’re committed to writing clean, readable, and well-documented code.
• BI & Visualization Tools - Hands-on experience with BI/dashboarding platforms (e.g. Looker, Tableau).
• Data Modeling Tools - Familiarity with semantic modeling tools (e.g. LookML) and dbt; understanding of ETL concepts. Experience with orchestration tools (e.g. Airflow) is a plus.
• Data Quality & Testing - Strong attention to detail in building data validation, profiling routines, and root cause analysis workflows
• Programming Skills - Experience with Python for data transformation, scripting, and automation; experience with associated libraries (e.g. pandas, openpyxl) is a plus
• Communication & Collaboration - Excellent interpersonal skills with experience working cross-functionally; ability to translate technical concepts for non-technical audiences and deliver training/support
• Educational Background & Experience - Bachelor’s degree in a quantitative, technical, or analytical field (e.g. Computer Science, Math, Physics, Engineering) or a rigorous coding bootcamp with a portfolio demonstrating the above skills