Senior 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 Senior Data Engineer at EDO, you will join a team of talented Data Engineers working closely with Data Scientists to build out our next generation Ad EnGage data pipeline. This pipeline measures and optimizes the effectiveness of advertising by combining and analyzing dozens of sources of advertising occurrence data, advertising outcome data, identity resolution data, and various other types of data. Our clients use these insights to make critical business decisions about their advertising strategy. You will work with large data sets (trillions of rows and hundreds of TB of data) using a modern tech stack centered on AWS, Airflow, DBT, and Snowflake.

• A minimum of 5 years of data engineering experience and three years of hands-on experience with cloud data platforms (preferably Snowflake or Redshift).
• Good working knowledge of data warehousing platforms (such as Snowflake, Redshift, etc), cloud computing (such as AWS), and ETL/data pipeline technologies (such as Airflow, DBT).
• Production experience building and operating complex and scalable data pipelines that optimize on data quality and are resilient to poor quality data sources.
• Strong experience with orchestration tools (Airflow strongly preferred) and dbt, including pipeline design, scheduling strategies, and failure recovery patterns
• Strong expertise in SQL, including query optimization/performance tuning, data modeling, schema design, and scalable data architecture.
• Proficiency in at least one scripting language, with Python preferred.
• Ability to work independently on loosely defined projects—gathering requirements and making architectural decisions that balance engineering constraints with business needs, while driving projects through to completion and production.

Bonus points:

• Previous industry experience working with TV or other advertising data is a plus.
• Familiarity with data security, privacy, including handling sensitive enterprise data, PII, and compliance-driven pipelines.
• Exposure to Data Clean Room concepts/implementation and Clean Room platforms like LiveRamp, Snowflake or Databricks.
• Exposure to identity/entity resolution and/or householding concepts/implementation.
• A strong understanding of software engineering practices, principles, and fundamentals.