Analytics Engineer

Summary

Imagine what you could do here! The people here at Apple don’t just create products — they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work. Do you have a strong passion for using data to drive business decisions, generate ideas, and inspire collaborators? As an Analytics Engineer on the Retail Store Analytics team, you will help create and maintain the analytic data pipelines that empower the analytics and reporting key to decision making across Retail. Leverage large and complex data sources from across Apple to deliver data products.

Minimum Qualifications

6+ years of industry experience building analytics pipelines in a production development environment Bachelor’s degree in a relevant field (Engineering, Data Science, Business) or equivalent experience 6+ years experience coding in SQL and Python 6+ years in data modeling and building robust and scalable data processes and pipelines for modeling, analysis, and reporting Ability to initiate, refine, and complete projects with minimal guidance Ability to think critically and and collaborate cross-functionally with other data engineering, data science and analytics stakeholders distilling abstract requirements into clear data products

Preferred Qualifications

3+ years of experience working with pipeline tools like Airflow and dbt 3+ years of experience in data observability building unit tests, anomaly detection and alerting solutions Experience translating business needs into logic and key performance indicators Experience with BI processes and some experience with dashboard tools like Tableau Master’s degree in a relevant field (Engineering, Data Science, Business) or equivalent experience

Description

You will partner with cross-functional teams to identify, create, and maintain metrics and data pipelines to support analytics, reporting, and key decisions on a wide variety of topics including product launches, customer experience, and operational performance. Other responsibilities include the following:
 Design, create, refine, and maintain data pipelines and ingestion processes used for modeling, analysis, and reporting. Collaborate with other data scientists, analysts, and engineers to build full-service data solutions. Work with cross-functional business partners and vendors to acquire and transform raw data sources. Develop a deep understanding of our retail customer base and purchase choices and contribute to the development of tools to improve business efficiency and productivity.

Responsibilities

Work with large volumes of data; extract and manipulate large datasets using tools such as SQL, dbt, command line and scripting languages. Analyze data covering a wide range of information from financial reporting to device purchase patterns such as export and trader activity and identify new patterns through data mining. Design, develop, validate and maintain big data-driven predictive models, tools and pipelines to improve device export predictions using latest technologies in machine learning. Use data observability tools to develop and manage and automate testing, alerting and improve data quality. Collaborate with data science, product, and engineering groups to translate business needs into data requirements, work with production teams to handoff reporting requirements for data products and communicate complex concepts and the results of the analyses in a clear and effective manner to business partners. Strong collaborative data engineering experience, including using version control, release management, requirements gathering, data testing and documentation.