Summary
Summary
Posted: Mar 23,
2021
Weekly Hours: 40
Role
Number:200190357
Imagine what you could do here. At Apple,
new ideas have a way of becoming great products, services, and
custom...Summary
Summary
Posted: Mar 23, 2021
Weekly Hours: 40
Role Number:200190357
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 engineers in Austin and Cupertino to build an analytics platform to support customer analytics with advanced, scalable and robust architecture, tools, data products, and critical data pipelines that are optimized for rapid business intelligence, data analysis, and data science.
Key Qualifications
- Proficient in SQL and at least one programming language (Java/Python preferred)
- 6+ years of experience in software and/or data engineering
- 3+ years of Spark development.
- 6+ years of experience in Big Data Technologies (Hadoop, MapReduce, Hive etc...). Spark experience preferred.
- Experience on Kubernetes, Docker preferred.
Description Develop and automate large scale, high-performance, scalable platform (batch and/or streaming) to drive faster analytics
Ability to design large-scale, complex applications and frameworks with excellent run-time characteristics such as low-latency, fault-tolerance and availability
Experience in building and maintaining custom frameworks to support engineering/analytics needs
Knowledge of continuous integration, testing methodologies, TDD and agile development methodologies.
Partner with analytic consumers and data scientists to build and improve new/existing constructs and solve data engineering problems @ scale.
Good knowledge of Data formats (Parquet, ORC etc.) and consensus management systems
Exposure to structured or unstructured storage and distributed caching.
Deploy inclusive data quality checks to ensure high quality of data.
Experienced Engineer or Contributor or Committer to open source technologies is plus.
Evangelize high quality software engineering practices towards building data infrastructure and pipelines at scale.
Structured thinking with ability to easily break down ambiguous problems and propose impactful solutions.
Communication Strong documentation and technical writing skills.
Attention to detail and effective verbal/written communication skills.
Education & Experience
BS/MS in Computer Science Quantitative Finance, Math, Physics or a related Engineering degree
Additional Requirements
