Solution Engineer, Data Operations

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, 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.

EDO is hiring a Solution Engineer to operate as a high-impact, hybrid problem solver across data engineering, analytics, and product. You will be the "technical fixer" responsible for solving urgent data issues, delivering rapid analysis, and building scalable solutions. If you enjoy jumping between debugging pipelines, analyzing data, and building quick prototypes — this role is for you.

• →Own urgent data and pipeline issues end-to-end.
• →Identify root causes and prevent recurring issues.
• →Debug data pipelines and model outputs.
• →Deliver fast, high-quality analysis for business and product needs.
• →Build POCs and data tools that scale over time.
• →Work across highly technical teams. (Engineering, Product, Analytical, TAM, Ops)

• 3-6 years in data engineering, operations engineering or similar roles.
• Strong preference for candidates with data engineering foundations.
• Experience in fast-paced, high-ambiguity environments.
• Strong proficiency in Python and SQL.
• Ability to ramp quickly in existing codebases. Experience with Airflow, dbt, Snowflake, or AWS is preferred.
• Experience in system support, incident response, or high-responsiveness technical environments.
• A track record of taking full accountability for projects and seeing them through to completion.
• Proven ability to solve problems in unclear, fast-paced situations.