Database Warehousing Specialist

Fox Corporation•Los Angeles, CA

1d•Hybrid

About The Position

As part of the AdRise team, Fox Cable Network Services, LLC seeks a Data Warehousing Specialist (Senior Data Engineer) to play an essential role in building and scaling the data management platform (DMP) and ads data systems. AdRise is Fox’s advanced technology platform for managing CTV and linear inventory. It powers OneFox, which is a cross-portfolio inventory product across Fox Sports, Fox Entertainment, Fox News Media, and Tubi. The position will lead the development of high-performance data pipelines that ingest, transform, and activate identity, audience, and ad delivery data.

Requirements

Requires a Master’s degree in Computer Science or related field, plus two (2) years of data engineering experience including designing and maintaining ETL pipelines within the AWS ecosystem
CI/CD automation for data and ML (Machine Learning) projects using CodeBuild, CodePipeline or GitHub Actions
Working with AWS services such as S3, Lambda, API gateway and EMR
Experience with cloud-based data platforms such as Databricks, Snowflake and Amazon Redshift
Knowledge of SQL, Python and Apache Spark
Knowledge of data integration and data transformation techniques
Experience working in an Agile development environment
Knowledge of data warehousing concepts, data modeling and schema design
Experience using MLflow and SageMaker

Responsibilities

Design, build, and maintain scalable data pipelines to support the ingestion, transformation, and activation of identity, audience, and advertising data.
Integrate with external identity resolution solutions and data partners to enable audience targeting and segmentation.
Develop data workflows that support ad delivery, campaign performance tracking, and cross-platform reporting.
Build and maintain attribution pipelines that connect first-party and third-party signals to media engagement and conversion events.
Ensure data infrastructure meets standards for quality, reliability, and governance using modern engineering best practices.
Collaborate with teams across engineering, product, and data science to define requirements and deliver actionable data solutions.
Use cloud-based tools and services such as AWS, Databricks, Snowflake, and Redshift to implement robust, production-ready workflows.