Analytic Engineering Lead - Product Marketing Customer Analytics
Santa Clara Valley (Cupertino), California, United States
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. 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.
- Significant experience leading a team of analytic engineers.
- Experience in designing, developing, and managing a highly optimized, flexible, and scalable analytics platform and data science pipeline.
- Ability to create value from highly connected, big data platforms.
- Can work closely with the analytics and data science teams to optimize data discovery, business intelligence, reporting, and modeling capabilities.
- Significant experience managing engineering projects through all phases, from design and analytic-based data optimization, to deployment, support, and training.
- 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.
- Experience with business intelligence and data visualization systems.
- Experience with advanced data modeling in support of an analytics platform.
- Able to work effectively on sometimes ambiguous data and constructs within a fast changing environment, tight deadlines and priority changes.
- Project management and communication skills with the ability to present work to senior management.
- Solid 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.