New York, NY US
Disney Streaming Services is a place for the creative and the bold. We're seeking talent across disciplines to join our team. Whether New York City, San Francisco, Manchester or Amsterdam we provide opportunities to elevate your career and transform an industry.
Software Engineers at Disney Streaming Services develop premium digital media products for Major League Baseball and our partners. The products we build, such as ESPN+, Disney+, MLB.TV and NHL.TV, are paving the way for the next-generation media and sport technologies. Our Engineering team for Disney Streaming Services is headquartered in the Chelsea area of New York City. Other office locations also include the SoMo area of San Francisco, CA and several international locations.
At Disney Streaming Services data is central to measuring all aspects of the business, and critical to its operations and growth. The data engineering team is responsible for data acquisition, real-time and stream processing, analysis, and distribution of data for further use using public cloud and open source technologies and offers transparency into customer behavior and business performance.
If you are interested in joining Disney Streaming Services in the pursuit of not only crafting new media products but enjoying the products you build, we are interested in hearing from you.
• Collaborate with product teams, data analysts and data scientists to design and build data-forward solutions
• Design, build and deploy a streaming data platform capable of processing and storing petabytes of data quickly, correctly and reliably
• Integrate with a variety of data metric providers ranging from advertising, web analytics, and consumer devices
• Drive and maintain a culture of quality, innovation and experimentation
• Collaborate with other teams, evangelize the platform, establish best-practices, influence data driven decisions, identify new use cases and features and drive adoption
• Coach data engineers best practices and technical concepts of building large scale streaming data platforms
• Grow a team of engineers, be a leader in the areas of code quality, system design, reliability, performance, and more
• Design and architect innovative real-time data-driven solutions and lead architecture direction
• Lead implementation of use cases across various domains
• Promote the team, the product, and the company internally and externally via community engagements
• 13+ years of software engineering experience and recognized as a thought leader
• Scala and functional programming expertise
• Extensive knowledge and experience with distributed systems, their development, operations, observability
• Experience and understanding of deploying and running AWS-based data solutions and familiar with tools such as Cloud Formation, IAM, Kinesis, S3, Firehose, EMR etc.
• Experience with devOps and building automation and reliability in large scale systems, including tools such as Jenkins, Docker, EC2, ECS, Cloudwatch, or languages like Python and Go
• Understanding of metadata management, data lineage and principles of data governance
• Experience with streaming data pipelines using Kafka, Spark, Storm, Flink, Pulsar or similar
• Deep expertise of AWS or other cloud technologies
• Experience with management of structured and semi-structured data in the context of streaming
• Experience with schema registry and data control plane components, data governance, data quality management
• Knowledge and experience building high quality Scala SDKs, utilizing functional programming patterns
• Knowledge of Big Data technologies and integration between streaming and batch processing, data convergence
• Skilled in binary data serialization formats such as Protobuf, Parquet, Avro or Thrift
• Experience building streaming data platforms, solving problems including event definition, evolution, processing, patterns and best practices, scalability, reliability, observability, validation etc.
• Knowledge and firm understanding of the data and streaming data ecosystems
Bachelor's degree in Computer Science or related field or equivalent work
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