Data Engineer II: Build Scalable Pipelines for ML

The Walt Disney Company; Beaverton (OR); Presencial; USD 112 000 - 150 000; Tempo integral

Resumo da oferta

Disney Entertainment and ESPN Product & Technology is seeking a Data Engineer II to turn large-scale data into reliable inputs for ML and viewer experiences.

You'll collaborate with ML engineers, data engineers and software engineers to build scalable data pipelines, while owning critical data features for recommendations. This role requires strong Python/Java skills, Databricks experience, and cloud platform familiarity across AWS, Azure, or GCP.

Qualificações

• Bachelor's degree in Computer Science or equivalent experience.
• 3 years of experience with large-scale data workloads and building data pipelines.
• Proficient in Python or Java.
• Experience with Databricks.
• Experience with cloud providers (AWS/Azure/GCP).

Responsabilidades

• Design, craft and own high-quality foundational datasets for ML inputs.
• Source, analyze and validate diverse upstream data sources from partner teams.
• Identify and build new user and content data features for recommendation systems.
• Enhance feature quality through experimentation and analysis.
• Build, optimize and maintain large-scale data processing jobs and pipelines.
• Improve data quality with checks, monitoring and alerting.
• Participate in on-call rotation to support critical production data pipelines.

Conhecimentos

Python/Java programming

Strong communication skills

Cloud platforms

Data engineering

CI/CD

Formação académica

Bachelor's degree in Computer Science

Ferramentas

Databricks

Apache Spark

Kafka/Kinesis

NoSQL databases

Descrição da oferta de emprego

Disney Entertainment and ESPN Product & Technology is seeking a Data Engineer II to turn large-scale data into reliable inputs for ML and viewer experiences.

You'll collaborate with ML engineers, data engineers and software engineers to build scalable data pipelines, while owning critical data features for recommendations. This role requires strong Python/Java skills, Databricks experience, and cloud platform familiarity across AWS, Azure, or GCP.