Software Development Engineer - Applications

APPLE INC has the following available in Seattle, Washington. Develop new algorithms to process large scale data efficiently. Gather cross-functional requirements specifically focused on enhancing streaming quality. Deliver and optimize the streaming content for Apple TV & Sports services and translate them into practical engineering tasks including optimizing content delivery algorithms and improving real-time data analytics processes. Collect, analyze, and build insights and report on customer experience data using Spark and Hadoop with the aim of enhancing user engagement and satisfaction through data-driven improvements in streaming services. Work on a small team and process large amounts of data and develop platform to process, analyze and mine that data to extract intelligence. Generate insights into how customers interact with our products and use these insights to drive improvements to user-facing features. Prepare data for visualization, ad-hoc exploration, reporting and further analysis, employing tools like Tableau for effective data presentation. Build large scale data processing, mining and analysis projects and features, ensuring robust and maintainable solutions are implemented with special attention to data quality, performance and usability details. Use knowledge of Cassandra, Kafka, Apache Flink, Computer Science algorithms and Data to create efficient, scalable data processing systems. These systems are vital for supporting the real-time analytical demands of the Apple TV & Sports services. Classify data and use experience with clustering algorithms in distributed environment. Programming using Java and Scala is essential for building and maintaining scalable and efficient data processing applications. Develop, advocate for, and build consensus on best coding practices. Provide support by contributing during design sessions. Explore new technologies and apply creative solutions to problems. 40 hours/week. At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $171,600 - $258,100/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits: https://www.apple.com/careers/us/benefits.html. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Bachelor’s degree or foreign equivalent in Computer Science or a related field and 2 years of experience in the job offered or related occupation. 1 year of experience with each of the following skills is required: Developing algorithms to process large scale data specially tailored for streaming services including proficiency in using Java, Scala and Python. Collecting, analyzing, and building insights, and reporting on customer experience data using Spark and Hadoop. Using Cassandra, Kafka, Apache Flink, Computer Science algorithms and Data Structures to manage real-time data pipelines and ensure data integrity in the context of streaming services. Classifying data and using experience with clustering algorithms in distributed environments, applying these methods to user behavior analytics in streaming services. Programing using Java and Scala to develop scalable and efficient data processing applications for content analysis and recommendation systems. Utilizing Hive for data warehousing and SQL-based querying in the streaming content domain. Implementing applications on HBase or Cassandra for real-time read/write access to large datasets related to viewer analytics. Managing distributed messaging and streaming processing using Kafka, crucial for real-time analytics in the context of live sports events and entertainment. Data visualization skills to create interactive dashboards that support strategic decisions in content programming and marking for streaming services N/A

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