Summary
Imagine what you could do here! The people here at Apple don't just create products — they create 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. Join Apple, and help us leave the world better than we found it. Apple's Worldwide Channel Strategy & Operations (WW CSO) organization focuses on developing and deploying worldwide sales programs and best practices to deliver an extraordinary customer experience in the channel and drive Apple Channel sales. With deep functional expertise in digital, physical, and people enablement spaces, our WW CSO team closely collaborates with many cross-functional groups at global and regional levels. We are seeking an experienced Senior Data Engineer to drive data ingestion, aggregation and visualization efforts for our channel sales platforms. This role will be critical in scaling how we ingest and transform data, from digital and in-store platforms to build a comprehensive view of the business. In this position, you will closely collaborate with multi-functional teams including regional sales teams, engineering teams, as well as external partners, to build data pipelines using advanced ETL capabilities and Cloud Data Infrastructure.
Key Qualifications
- 8+ years experience building highly scalable, compliant, and secure, enterprise-grade data and analytics platforms with robust data quality, data governance, data discovery, catalog and visualization capabilities
- 4+ years of experience working with large-scale e-commerce data and analytics platform, including building pipelines for Digital performance KPIs, Performance Marketing, and Testing & Optimization
- Strong coding knowledge / abilities in handling large data sets through SQL, data manipulation and ETL tools such as Alteryx; and experience with using cloud data platforms such as Snowflake and Amazon S3
- Experience building data pipelines in production and ability to work across structured, semi-structured and unstructured data
- Proven understanding of the enterprise data concepts (Master Data, Operational Data, Reference Data, Transactional Data)
- Hands on experience with the latest OSS, cloud, container, query languages and database technologies
- Solid understanding of security and risk principles around data, including governance and architecture considerations
- Strong expertise in implementing effective and successful Cloud based Data Migration and Data Integration strategies across ERP systems
- Good understanding of data warehousing, data lake concepts and Tableau dashboards (including Tableau Prep), visualizations, etc.
- Proven track record in enterprise-wide API management, micro-services, event-driven architectures and complex integrations
- Entrepreneurial attitude with an ability to navigate ambiguity while being able to "focus on what matters most"
- Strong influencing skills that drive alignment with a wide range of partners in a non-hierarchical environment, including business, operational and technical teams
- Programming skills in R or Python, a plus
- Commercial experience in a data-driven role, a huge plus
- Relevant certifications in AWS or other cloud data platforms preferred
- Experience with Marketing Analytics Platform such as Salesforce Datorama, a plus
Description
In this role, you will focus on the following key areas :
Data Pipelines : Build sustainable data pipelines and curated data sets needed to for business use-cases across multiple sources (operational, analytical and reporting)Data Quality : Conduct data assessment, perform data quality checks and transform and load raw data into Cloud Data Hub using SQL and ETL tools such as DataikuData Definition : Manage data lifecycle including definition, usage and quality using architecture repositories like data dictionaries, data models, metadata and data quality logsKPIs : Responsible for assembling and maintaining the data sets enabling the suite of Digital and Physical Performance metricsGovernance : Partner closely with technology partners and internal engineering teams on data architecture, standardization, and curation for prioritized use-casesTeamwork : Collaborate with GEO business and technical partners and teams to analyze needs and develop data integration solutionsRoadmap : Contribute to overall Data and Analytics strategy and roadmapEducation & Experience
Ph.D. in Computer Science, Machine Learning, Statistics, Operations Research or related field; or Ph.D. in Math, Engineering, Economics, or hard science with data science fellowship; or M.S. in related field with 3+ years experience applying machine learning engineering to real business problems
About the company
Work at Apple! Join a team and inspire the work. Discover how you can make an impact : See our areas of work, worldwide locations, and opportunities for students.
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