Overview

OVERVIEW OF THE COMPANY Fox Corporation

Responsibilities

• About FOX Corporation:
• FOX Corporation is a leader in the entertainment and media industry, delivering innovative content through our news, sports, and entertainment brands. With a dynamic portfolio that includes FOX News, FOX Sports, and the FOX Television Network, we reach millions of viewers across various platforms every day. At FOX, we aim to entertain, inform, and connect people around the globe, all while shaping the future of the media landscape.
• About FOX Emerging Tech:
• Our team is dedicated to fostering creativity and building scalable solutions that empower FOX to thrive in a rapidly changing digital world. Whether it’s pioneering new platforms, enhancing user experiences, or creating tools for next-gen content, FOX Emerging Tech is shaping the future of entertainment.
• About the job:
• We believe in the future of entertainment – across all platforms and for all audiences.
• FOX has always given unfettered access to the moments that have collectively captivated us. The breaking story. The unmissable final. The outrageous touchdown. The shocking cliffhanger. We changed the game on sports and news production. Now we’re looking to change the game again.
• We are pioneering the future of news, sports and entertainment in the digital realm. It’s an audacious mission. We’re challenging ourselves to be the first to do it - to disrupt the digital entertainment category and redefine the live experience for the next generation. And we’re doing it by starting from scratch.
• A Snapshot of Your Responsibilities
• Design and Develop: Develop robust data ingestion, transformation, and processing frameworks using technologies such as Databricks, Spark, Kafka, Airflow, DBT, and cloud-native services. Build and optimize data models, lakehouse architectures, and data products that serve analytics, reporting, machine learning, and operational use cases.
• Collaboration: Partner closely with product managers, analysts, data scientists, and software engineers to understand business requirements and translate them into scalable data solutions.
• Security and Governance: Ensure all data systems adhere to security, privacy, and governance requirements. Implement best practices around access controls, encryption, data lineage, and compliance.
• Documentation and Quality: Create and maintain technical design documents, data flow diagrams, source-to-target mappings, and operational runbooks. Develop comprehensive testing strategies and automation to ensure reliability and correctness of data products.
• What You'll Need:

Qualifications

• Strong experience building data platforms using Databricks, Snowflake, or modern cloud-native data ecosystems.
• Hands-on expertise with Python, PySpark, SQL, and distributed data processing frameworks such as Apache Spark or Flink.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field with at least 4+ years of experience building large-scale data engineering solutions and data platforms.
• Strong understanding of dimensional modeling, data warehousing, and lakehouse architecture patterns.
• Problem Solving: Strong analytical and troubleshooting skills with the ability to identify bottlenecks, optimize performance, and solve complex data challenges at scale.
• Design: Experience designing scalable, resilient, and observable data systems with a strong focus on reliability, performance, and maintainability.
• Data and AI Enablement: Experience building data foundations that support advanced analytics, machine learning, and AI-driven applications. Exposure to modern data and AI platforms such as Databricks, MLflow, SageMaker, Vertex AI, or similar ecosystems is highly desirable.
• Ownership and Accountability: Self-driven mindset with a strong sense of ownership. Ability to take initiatives from concept through production deployment and ongoing operational support.
• Communication: Excellent communication and collaboration skills with the ability to work effectively across technical and non-technical stakeholders.
• Good to Have
• Knowledge of data governance, cataloging, lineage, and metadata management solutions.
• Open-source contributions or active participation in the data engineering community.
• Interest in emerging technologies including AI, machine learning, and modern data platform architectures.