Join Disney Entertainment and ESPN Product & Technology as a Senior Data Engineer I, playing a pivotal role in advancing the technological backbone for Disney's global media business. This is an opportunity to contribute to cutting-edge ad platforms, driving performance, innovation, and value across a wide range of Disney's beloved content.

Leverage your expertise to build and optimize scalable data pipelines that power major platforms like Disney+, Hulu, and ESPN. You'll be part of a dynamic team that merges technology with creativity, shaping the future of media delivery and fan engagement.

This role offers significant reach, scale, and impact, allowing you to work on products and platforms serving millions worldwide. If you're passionate about innovation and solving complex technical challenges within a leading entertainment company, this is the role for you.

As a Senior Data Engineer I, you will be instrumental in ensuring the reliability, scalability, and performance of Disney's big data platforms.

Key responsibilities include:

- Designing, maintaining, and optimizing data pipelines using Spark and Flink within Databricks and Airflow environments. - Ensuring the resilience and availability of production data workflows. - Debugging and resolving issues across notebooks, jobs, and orchestration workflows. - Tuning Spark jobs and clusters for optimal performance and cost efficiency. - Building and maintaining monitoring dashboards, alerts, and metrics using tools like Datadog. - Participating in incident response, diagnosing issues, and contributing to root cause analysis for improved long-term stability. - Collaborating with cross-functional teams, documenting best practices, and mentoring junior engineers.

We are seeking a seasoned Senior Data Engineer I with at least 4 years of experience in data engineering or big data platform operations.

Essential qualifications include:

- Hands-on experience with production environments using Databricks, Spark, Flink, or Airflow (MWAA). - Strong proficiency in SQL and extensive experience in ETL/ELT pipeline development. - Familiarity with AWS services such as S3, Glue, Athena, EMR, and EKS. - Working knowledge of observability tools including Datadog, CloudWatch, and Prometheus. - Proficiency in Python, Scala, or Java for pipeline development and automation. - A Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. - Excellent collaboration and problem-solving skills, especially within distributed team settings.