Senior Data Engineer

EDO is the TV outcomes company, specializing in connecting TV airings to consumer behaviors predictive of sales. The Senior Data Engineer will work with a team to build and optimize the Ad EnGage data pipeline, analyzing various data sources to inform clients' advertising strategies.

Responsibilities:

• Join a team of talented Data Engineers working closely with Data Scientists to build out our next generation Ad EnGage data pipeline
• Measure and optimize 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
• 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

Requirements:

• 6+ 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
• 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