Data Engineering Lead - Product Marketing Customer Analytics

Santa Clara Valley (Cupertino), California, United States


Weekly Hours: 40
Role Number:200109525
Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. *There is a possibility of this position being located in Austin, TX* The Product Marketing Customer Analytics team is seeking a lead data engineer to support customer analytics with data architecture, data pipelines, and process engineering across relational databases and big data platforms.

Key Qualifications

  • Significant experience leading a team of data engineers.
  • Experience in designing, developing, and managing a highly optimized, flexible, and scalable data platform for customer analytics.
  • Experience building a connected data platform, and stitching together various large and disparate data sources for data analysis.
  • Significant experience managing data engineering projects through all phases, including requirements, ETL, data quality assessments, and data exploration.
  • Strong in Python, Spark, and Hadoop environments.
  • Deep experience with relational databases and data warehouses (preferably Teradata), and optimizing SQL statements on large data set.
  • Able to deploy advanced data quality monitoring systems to ensure continuous accurate information.
  • Ability to work cross-functionally with business partners, source system teams, and IT partners.
  • Can work effectively on sometimes ambiguous data and constructs within a fast changing environment, tight deadlines and priority changes.
  • Solid debugging, critical thinking, project management, and communication skills with the ability to present work to senior management.
  • Strong documentation and technical writing skills.


The Product Marketing Customer Analytics team is seeking a lead analytic engineer to support customer analytics with advanced architecture, tools, data products, and pipelines that are optimized for rapid business intelligence, data analysis, and data science.

Education & Experience

Prefer: Master’s in Computer Science or Engineering, or equivalent experience.

Additional Requirements