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Senior Software Engineer

Fox Corporation

OVERVIEW OF THE COMPANY Fox Corporation

Under the FOX banner, we produce and distribute content through some of the world’s leading and most valued brands, including: FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations and Tubi Media Group. We empower a diverse range of creators to imagine and develop culturally significant content, while building an organization that thrives on creative ideas, operational expertise and strategic thinking.

JOB DESCRIPTION

AdRise is the ad platform that powers FOX. The Data Management Platform (DMP) team builds the identity, audience, and activation systems that turn 100M+ monthly viewers across Tubi and the broader Fox portfolio into privacy-conscious, high-value targeting for advertisers. FOX's monetization depends on the audiences this team can define, size, and activate.

At the center of that work is Audience Builder: the large-scale compute platform that transforms billions of identity and attribute records into reusable audiences to activate to various ad servers, including our in-house ad server within AdRise. Architectural decisions ripple across billions of IDs and millions of dollars of ad revenue.

We're looking for a builder who wants to own systems that sit on the critical path of the ad business, range across the stack from Spark batch pipelines to the control-plane API and emerging AI agents, and see their work felt directly by advertisers, ad ops, and the bottom line.

A SNAPSHOT OF YOUR RESPONSIBILITIES

We are looking for flexible software engineers who can work in multiple domains: core services development, data pipelines, performance optimization, and more.

  • Design, build, and scale distributed Scala/Spark pipelines on Databricks that compute audience membership over billions of identifiers.
  • Evolve the Audience Builder platform end to end, including attribute ingestion, identity mapping, audience creation, and activation to ad platform destinations.
  • Model and manage large Delta Lake tables with careful attention to partitioning, idempotent writes, and reprocessing at scale.
  • Optimize cost and performance: we have huge Spark workloads on 100+ node clusters, and low-latency services that process thousands of QPS.
  • Collaborate with Data Platform team to define data contracts to meet business needs.
  • Integrate with the in-house AdRise ad platform stack.
  • Ensure the operational success of the team by refining processes and participating in the team's oncall rotation.

Key Responsibilities

  • Develop and enhance distributed systems for high availability, scalability, and operability at ad-tech scale.
  • Design data models, bitmap encodings, and APIs that serve product UIs, analytics, and increasingly AI agents as first-class clients.
  • Partner with ad ops, data science, and business teams to create the tools that turn audience definitions into activated, revenue-generating segments.
  • Operate partner integrations that determine which audiences are available on which platforms.
  • Own quality, correctness, and performance of audience sizing and reporting that advertisers and internal stakeholders depend on.

WHAT YOU WILL NEED

  • 6+ years of experience building production data or backend systems.
  • Strong programming skills in Scala, or a strong background in another JVM/functional language.
  • Hands-on experience with Apache Spark (or comparable large-scale distributed compute) and columnar/lakehouse formats such as Delta Lake, Parquet, or Iceberg, particularly on Databricks.
  • Solid understanding of distributed systems, data modeling, partitioning, and performance tuning at scale.
  • Experience integrating with external APIs and building reliable batch or streaming pipelines.
  • Bachelor's or Master's degree in Computer Science or a related field, with equivalent industry experience (exceptions made for exceptional candidates).

We will consider remote candidates for this role.

#Ll-KD1

#Adrise

#Ll-Hybrid

Learn more about Fox Tech at

#foxtech

Vacancy posted 2 days ago
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