The Siri Attention and Invocation Data team is in search of a curious and innovative team player who is passionate about building and innovating our data strategy. Our team is responsible for all aspects of generating datasets to improve and innovate our user experiences. Join Apple and help us leave the world better than we found it!

You will be a core contributor on the development of our data pipeline and management systems, as well as spearheading innovative approaches to improving different aspects of our data. Your responsibilities will include:

• Working closely with other teams to understand their needs and propose ways to address them, translating them into data products, workflows and services.
• Architect solutions for taking our pipelines, workflows and data management and exploration to the next level.
• You will play an active role in the future roadmap of our data strategy, by designing and implementing the next generation to improve data quality, cost-effectiveness, monitoring, traceability and introspection.
• Collect requirements and engage stakeholders from different teams, and to bring into production complex cross-functional projects.

Strong software engineering skills, including being fluent in Python.Attention to detail and creative problem-solving: Do you dig into the data to troubleshoot a problem?You have 4+ years’ professional experience in data engineering and data pipelines.You have 4+ years’ professional experience in system design and architecture.You have 4+ years’ professional experience leading complex projects and teams of engineers.You have 4+ years of hands-on experience building reliable, scalable Data Pipelines with Python in a scalable cloud environment (AWS, etc).Familiarity with some of the following: Postgres, Presto, REST API development, Spark, cloud development, numpy, pandas, to name a few.Strong technical communication (both written and verbal), prioritization, and time management skills. Strong interpersonal skills to work both with your team and others.Familiarity with Machine learning dataset development lifecycle.Bachelor’s Degree in Computer Science, an engineering-related field, or equivalent related experience.