Your New Role:

The Senior Staff Data Engineer is accountable for designing and delivering data pipelines that process billions of ad events daily across WBD's global ecosystem. This role sets technical standards for distributed data engineering, drives modernization of legacy workflows into modular cloud-native systems, and ensures mission-critical data is delivered reliably, securely, and cost-efficiently for monetization and decisioning.

Your Role Accountabilities:

High-Scale Data Pipeline Engineering
• Design and maintain ingestion, ETL, and activation pipelines supporting real-time and batch processing of multi-billion event datasets.
• Optimize data workflows for latency, reliability, and scalability in cloud-native environments.

Platform Modernization & Lakehouse Development
• Modernize legacy ad-tech systems into open, lakehouse-based architectures (Iceberg, Delta, Hudi) for unified analytics and monetization.

Embed observability, data lineage, and automation frameworks to reduce technical debt and improve resiliency.

Cross-Functional Data Delivery
• Partner with Data Science to operationalize ML models for forecasting, optimization, and personalization.
• Ensure downstream data delivery into ad servers, identity systems, and activation platforms is low-latency and privacy-compliant

Architectural Leadership & Mentorship
• Act as a domain expert in distributed systems, streaming, and big data engineering.
• Mentor junior engineers, share best practices, and elevate engineering standards across global teams.

Qualifications & Experience
• Education: Bachelor's or Master's degree in Computer Science, Engineering, or related field. PhD preferred for advanced expertise in distributed systems or statistical optimization.
• Data Engineering Expertise: 12+ years of experience designing and operating enterprise-scale data platforms with high-throughput pipelines.
• Cloud & Lakehouse Architectures: Hands-on expertise with AWS/GCP/Azure, open table formats (Iceberg, Delta, Hudi), and distributed compute (Spark, Flink, Presto).
• Streaming & Real-Time Systems: Deep knowledge of Kafka, Kinesis, or Pub/Sub for powering low-latency ingestion and activation.
• Operational Excellence: Skilled in CI/CD, automation, observability, and governance frameworks for enterprise-grade data engineering.
• AdTech Domain Knowledge: Familiarity with advertising workflows including forecasting, yield optimization, identity, and campaign execution.
• Collaboration & Mentorship: Demonstrated ability to partner with data scientists, product, and platform engineering, while mentoring junior engineers.

#LI-Hybrid