Cupertino, California, United States
Summary
Weekly Hours: 40
Do you get excited by driving impact via measurement and evaluation, for products and services used by hundreds of millions of people globally? The vision of AIML Data and ML Innovation organization is to improve products by using data as the voice of our customers. We are seeking a passionate and experienced Data Infrastructure Engineer to play a pivotal role in revolutionizing how we process and use substantial datasets as the heart of Siri, Search and Machine Learning. You will be instrumental in building a unified, groundbreaking data insights framework and data processing framework, powered by technologies such as Spark or Iceberg. You will collaborate closely with teams with varied strengths (i.e. Data Scientists and Analysts, other Engineering teams) to transform massive data into valuable, actionable datasets. You will also build metrics platform that fuel our innovative features and future machine learning area.
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Description
As a Data Infrastructure Engineer, you will be at the forefront of designing and implementing a robust data processing framework to streamline log data pipelines, and a flexible data insights infrastructure, applying your expertise in Spark and Python. In this collaborative role, you’ll partner closely with the Siri, Search, and other teams to design solutions that process data and build metrics platform, which drive innovation. Your work will focus on optimizing performance, ensuring data quality, and contributing to a long-term vision that extends the existing framework’s capabilities to new user scenarios and innovative machine learning applications. We’re looking for someone who thrives on tackling data challenges at scale and stays abreast of the latest advancements in big data processing on both device and server side.
Minimum Qualifications
- Demonstrated expertise in large-scale data processing, with a strong background of working with Spark and Python or Scala.
- Understanding of distributed computing principles, data engineering and DevOps standard processes.
- Proven programming skills in Python and Scala.
- A genuine passion for working with data and solving complex problems at scale, in cloud platforms (AWS, GCP).
- Experience with machine learning data mining.
- B.S.degree in Computer Science or Data Science.
Preferred Qualifications
- Metrics infrastructure experience, including metrics sharing, management, version control.
- PhD or MS in Computer Science.
Pay & Benefits
- 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 $175,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.
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.
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