Data Engineer, Find My
The Find My team is dedicated to building a seamless, private, and secure experience for users to locate their devices, personal items, and share location with friends and family. We're a group of highly motivated engineers, designers, and product managers who are passionate about creating a simple and reliable experience for hundreds of millions of users worldwide. We thrive in a fast paced environment where team members are often encouraged to wear multiple hats and contribute to various aspects of the product lifecycle. Innovation and creative problem-solving are at the heart of our team, and we constantly explore new approaches to deliver groundbreaking solutions while collaborating with diverse disciplines across the company, including hardware, software, and privacy, to deliver an exceptional user experience.
Description
As a Data Engineer on our team, you'll thrive in a fast-paced, startup-like environment, collaborating closely with a passionate cross-functional team to transform complex data into insights that power our shared mission. You'll be instrumental in designing and building the analytics pipelines behind exciting new features, and your contributions will directly impact millions of users. We embrace continuous iteration and improvement, so you'll have the opportunity to learn, grow, and refine your skills as we build the future of Find My.
You will translate analytics needs from Data Science, Engineering, Product, and Program Management into high-quality, well-modeled data artifacts. Developing methods to monitor data quality and balancing competing priorities will be key to your success. You will dive deep into complex data engineering problems to ensure our solutions are extensible, reliable, and ready to deliver at scale.
Preferred Qualifications
Experience with open table formats such as Delta Lake or Apache Iceberg
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Experience with Spark on Kubernetes
Experience with data quality monitoring and anomaly detection
Familiarity with BI/visualization tools (e.g., Superset)
Familiarity with privacy-preserving data engineering techniques
Experience with machine learning applied to the domain of data engineering and analytics
Minimum Qualifications
BS in Computer Science, Data Engineering, or related field
10+ years of experience working with large data sets and dimensional data modeling
10+ years of experience with data processing using Spark and SparkSQL
Experience with data pipeline orchestration tools
Expertise in Java or Scala, and experience with Python
Experience with Amazon Web Services, GCP, or Azure
Strong communication and collaboration skills","internalDetails":null
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 $147,400 and $272,100, 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. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Perks and Benefits
Health and Wellness
Parental Benefits
Work Flexibility
Office Life and Perks
Vacation and Time Off
Financial and Retirement
Professional Development
Diversity and Inclusion
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