Data Engineer- Maps

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we Are you ready to take Apple Maps Analytics Platform to next level? We in Maps Analytics Platform team partner closely with Data Scientists, Program Managers and Product Analysts to measure and improve Apple Maps user experience. You will work with some of the most unique and interesting data sets in the world including: geospatial data, GPS probe data, search logs, real time traffic data, and A/B experiments data. Description You will be contributing to our large scale data platform and providing end-to-end analytics solutions to transform rich data at Apple scale into actionable insights. Your work will help us build extensible processing and storage solutions that deliver data products for the entire Apple Maps. The insights from your data products directly impact millions of Apple customers world wide. We are looking for an engineer who loves to build end to end solutions for their customers and can produce high quality data artifacts at scale. The ideal candidate has experience implementing extendable frameworks on top of Spark and understands the inner workings of Spark execution and cloud computing. RESPONSIBILITIES: - Partner with Program, Data Science and Engineering -teams to understand Apple Maps analytics data needs - Design and build data processing pipelines in a hybrid cloud environment - Design data models for optimal storage and retrieval - Design and develop new data processing systems to enable quick and easy consumption and augmentation of data - Build data expertise and develop methods to monitor data quality

Minimum Qualifications

• 4+ years of experience in working with large data sets and dimensional data modeling
• Deep experience with schema design and dimensional modeling
• 4+ years of experience with data processing using Spark and SparkSQL
• Experience with SQL or other declarative data extraction languages
• Advanced skills in Java or Scala

Preferred Qualifications

• B.S or advanced degree in Computer Science or related field
• Experience in big data processing platform and framework development
• Experience with Amazon Web Services, Google Cloud Platform or Azure
• Experience with Databricks, Spark on Kubernetes or EMR
• Experience with real time data processing using Kafka and Storm or Spark Streaming

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 $143,100 and $264,200, 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. 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. Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . Apply Job!