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Lead Data Engineer, Data Platform 571 views

Disney Streaming Services is a place for the creative and the bold. Whether New York City, San Francisco, Manchester, or Amsterdam, they provide opportunities to elevate your career and transform the industry.

Software Engineers at Disney Streaming Services develop premium digital media products for Major League Baseball and their partners. The products they build, such as ESPN+, Disney+, MLB.TV and NHL.TV, are paving the way for the next-generation media and sport technologies. Data Engineering’s mission is to provide a robust data ecosystem that enables data producers and data consumers to connect in order to provide operational and analytic transparency for their rapidly growing business. To that end, the Data Platform team is responsible for building the tools and services that empower their users to make data-driven technical and business decisions and democratize data across the organization.


  • Collaborate with product teams, data analysts, and data scientists to design and build data-forward solutions
  • Design, build, and deploy streaming and batch data pipelines capable of processing and storing petabytes of data quickly and reliably
  • Build and maintain tools and services to support data ingestion, discovery, lineage, and ETL
  • Build and maintain dimensional data warehouses in support of business intelligence tools
  • Develop data catalogs and data validations to ensure clarity and correctness of key business metrics
  • Drive and maintain a culture of quality, innovation, and experimentation
  • Coach data engineers on best practices and technical concepts behind large-scale data platforms
  • Provide technical vision for DSS data platform, leading all technology and system design/architecture decisions
  • Lead implementation/realization of the aforementioned technical vision
  • Work in an Agile environment that focuses on collaboration and teamwork
  • Evangelize Data Platform throughout the Disney Streaming Services organization

Basic Qualifications

  • Experience developing in one or more of the following: Python, C++, or any JVM language
  • Experience deploying and running cloud-based data solutions (AWS, GCP, Azure) and familiar with tools such as CloudFormation, Kinesis, ECS, S3 (or equivalent)
  • Experience engineering big-data solutions using technologies like Databricks, EMR, and Spark
  • In-depth understanding of data partitioning and sharding techniques
  • Familiarity with metadata management, data lineage, and principles of data governance
  • Experience loading and querying cloud-hosted databases such as Redshift and Snowflake
  • Experience building streaming data pipelines using Kafka, Spark, Flink, or Samza
  • Experience with API design

Preferred Qualifications

  • Experience with functional programming in Scala
  • Experience building distributed systems with microservices and/or service-oriented architectures
  • Familiarity with containerization/virtualization, e.g., Docker
  • Knowledge of CI/CD best practices
  • AWS experience
  • Familiarity with binary data serialization formats such as Parquet, Avro, and Thrift
  • Experience deploying data notebook and analytic environments such as Jupyter and Databricks
  • Experience with graph-based data workflows using Apache Airflow

Required Education

  • Bachelor’s degree in Computer Science or related field or equivalent work experience

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