Position overview
This position reports to the Senior Data Analytics Engineer; it will behave cross functionally across Data teams with an emphasis on supporting the Analytics team and their workflows.
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.
We’re seeking a candidate with 0-2 years of experience in analytics, data engineering, or a related field, and a passion for building clean, reliable data systems.
This is a fully remote position within the United States, with opportunities to connect with colleagues at our New York office. You will need to be in NYC a few times per year.
Compensation
- Base Salary Range: $80,000-$100,000
This role includes a competitive compensation package consisting of base salary, performance-based bonus, and equity. Final compensation will be determined based on experience, level, and location.
What you'll learn
An important part of our culture is continuous learning and the open sharing of ideas. We offer:
- Access to a broad network of investors and advisors who can help you and your team succeed
- Mentorship from executives with decades of experience in adtech and media
- Regular internal knowledge-sharing sessions
- An education budget to support ongoing professional growth and development
In this role you'll 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
- Contribute to maintaining a well-organized data catalog with accurate, accessible metadata for both technical and non-technical audiences
- Build, test, and maintain SQL-based data models in the data warehouse (Redshift) to support reporting and analytics
- Help create and manage a clean, reliable reporting and semantic layer in Looker using LookML, ensuring business logic and metrics are clearly defined and reusable across dashboards
- Work cross functionally across Account Managers, Customer Success, and Analytics to support reporting needs and improve data accessibility
- Monitor data adoption and identify opportunities to improve data usability and self-service analytics
What you'll bring
- SQL Proficiency - Strong ability to write, optimize, and debug SQL queries. You understand data modeling and warehouse best practices and are committed to writing clean, readable, and well-documented code.