Staff Engineer

About the role

Welcome to Warner Bros. Discovery… the stuff dreams are made of.

Responsibilities

• Design and deliver API-first, cloud-native services that enable real-time interoperability across WBD’s advertising stack, handling billions of impressions annually.
• Modernize legacy advertising tools into modular, cloud-native applications with 99.99% reliability, optimized costs, and seamless integration with converged platforms.
• Build and maintain services for ad-serving, campaign management, and identity systems. Develop APIs and integrations with third-party AdTech partners and data providers.
• Partner with product and operations teams to align technical solutions with business goals. Share best practices and mentor junior engineers when needed.
• Design and implement ETL pipelines and real-time data processing for ad performance, forecasting, and yield optimization. Work with big data frameworks (Spark, Kafka) to handle large-scale datasets.

Qualifications & Experience

• Educational Background: Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Engineering Expertise: 8+ years in software engineering, with exposure to AdTech or large-scale distributed systems.
• Technical Experience: Hands-on expertise with Java, Scala, or Python. Experience with cloud platforms (AWS/GCP/Azure). Strong knowledge of SQL and NoSQL databases. Familiarity with big data tools (Spark, Kafka) and streaming architectures.
• Cloud & APIs: Strong knowledge of cloud-native development (AWS, GCP, Azure), microservices, and API-first design.
• AdTech Domain Knowledge: Familiarity with advertising workflows including forecasting, yield optimization, identity, and campaign execution.
• Linear Systems Domain Knowledge: Experience with linear advertising, scheduling, trafficking, and broadcast operations platforms, including modernization into API-driven, cloud-native solutions.
• AI & Automation Systems Expertise: Demonstrated experience designing, building, and operating AI-driven automation and agent-based systems that integrate with large-scale distributed platforms, enabling reliable tool execution, workflow orchestration, observability, governance, and measurable improvements in engineering and operational efficiency at scale.
• Collaboration & Mentorship: Demonstrated ability to partner with data scientists, product, and platform engineering, while mentoring junior engineers.