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Apple Data Engineer United States, California, Cupertino 153992709
Today
APPLE INC has the following available in Cupertino, California and various unanticipated locations throughout the USA. Provide data and reporting requirements for new technology capabilities implemented within the platforms managed by the Channel Strategy and Operations team. Partner with Regional stakeholders to gather analytics use cases to support day-to-day operations. Identify new data points introduced within the platform, across each line of business supported and each operating system. Partner with Quality Assurance engineers to complete all data testing during new functionality user acceptance testing periods. Report any bugs and discrepancies with the engineering teams. Triage and follow up on bug fixes. Sign off on all data testing for completion and accuracy. Build and manage all operational dashboards and reports, measuring program compliance and expansion. Create logic required to calculate accurate reporting insights to inform business decisions or actions required. Validate dashboards and reports for data accuracy, fix issues, and follow up with required engineering teams as necessary. Train and onboard new users to the data set to create their own reports. Manage data dictionary for all data points for the Channel interactive technology systems. Run ad hoc data analysis using descriptive and predictive analytics models as business dictates. 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 $140,901 - $188,100/yr and your base pay will depend on your skills, qualifications, experience, and location.
- Bachelor’s degree or foreign equivalent in Mathematics, Statistics or related field and 2 years of experience in the job offered or related occupation. Employer will accept 3 or 4 year Bachelor's degree or foreign equivalent.
- 1 year of experience with the following skill is required:
- Experience with applying regression models (logistic, polynomial, and linear) and classification models (decision trees, bayes, and random forests) statistical approaches to solve business questions.
- 2 years of experience with each of the following skills is required:
- Using data manipulation and analysis to answer quantitative business questions
- Performing end-to-end validation of new data sets used for data analysis
- Using Tableau to provide stakeholders with easy to digest and actionable insights on pre-defined KPIs that impact their business
- Using Python to load, clean and prepare raw, structured and unstructured data for data analysis and visualizations
- Using SQL to gain access to the key data sources used for all analytics projects
- Experience with applying regression models (logistic, polynomial, and linear) and classification models (decision trees, bayes, and random forests) statistical approaches to solve business questions
- Forecasting future performance of channel locations using historical data and statistical models for stakeholders
- Experience extracting, transforming and cleaning data for data analysis: building data pipelines; querying against multiple database tables, combining information through joins;
- identifying and fixing incorrect, missing or incomplete data; data visualization or analysis through pivots, staking and unstaking; and uploading cleaned data sets to a database table.
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