Data Engineer

EDO is the TV outcomes company. Our leading measurement platform connects convergent TV airings to the ad-driven consumer behaviors most predictive of future sales. EDO empowers the advertising industry to maximize media impact, optimize creative performance, and know the fair value of every impression — across linear and streaming for an increasingly programmatic world. By combining immediate engagement signals with world-class decision science and vertical AI, EDO equips industry leaders with syndicated, investment-grade data that aligns media to business results — with detailed competitive, category, and historical insights. Leading brands, agencies, networks, streamers, and studios trust EDO’s TV intelligence to know what works.

EDO is headquartered in New York City and Los Angeles with an office space in San Francisco. We recognize the benefits of hybrid working, and want to create the best balance to ensure we can continue working together effectively. For those who reside full-time in NYC, SF, or LA: we have a hybrid work policy of three days in the office and two remote work days. 

To learn more about the work we do at EDO, please visit EDO Press.

As a Data Engineer at EDO, you will join a team of talented engineers working closely with Data Scientists to build and scale our next-generation Ad EnGage data pipeline. This pipeline measures and optimizes the effectiveness of advertising by combining and analyzing a wide range of datasets, including advertising occurrence data, outcome data, identity resolution data, and more. Our clients rely on these insights to make critical decisions about their advertising strategy.

You will work with large-scale datasets (hundreds of TBs to petabyte-scale systems) using a modern data stack centered on AWS, Airflow, dbt, and Snowflake. You’ll contribute to building reliable, high-quality data pipelines and improving the performance, scalability, and observability of our data platform.

• 3-6 years of experience as a Data Engineer. 
• Hands-on experience with cloud data platforms (Snowflake or Redshift preferred).
• Strong understanding of data warehousing concepts and cloud infrastructure (AWS preferred).
• Experience building and maintaining ETL/ELT pipelines using tools such as Airflow and dbt.
• Strong SQL skills, including query optimization, data modeling, and working with large datasets.
• Proficiency in at least one scripting language, preferably Python.
• Hands-on experience with large-scale, complex data pipelines operating at billions to trillions of rows of data. 
• Ability to work independently on well-scoped projects, collaborate with cross-functional partners, and deliver production-ready solutions.