Siri - Data Engineering Manager- Data Organization
Santa Clara Valley (Cupertino), California, United States
Software and Services
Would you like to play a part in the next revolution in human-computer interaction? Contribute to a product that is redefining mobile and desktop computing, and work with the people who built the intelligent assistant that helps millions of people get things done — just by asking? The vision for the Siri Data organization is to improve Siri by using data as the voice of our customers. Within this organization the mission of the Data Solutions Engineering team manages existing data resources, build new data pipelines, implement new technologies and tooling to further enable science and analytics, As the Data Engineering Manager you will build and lead our data engineering team and help the members of your team grow both technically and professionally. You will work closely with analytic and data scientist teams and lead the planning, execution and success of technical projects as well as help drive scalable data sharing practices to accelertate the evolution of Siri through measurement and analysis of the user experience. You will create a vision for data that will enable analytics to inform product and engineering teams at scale, with the ultimate purpose of improving the Siri experience for Apple customers.
- 6+ years of experience in data engineering.
- Expertise with leading, managing and hiring a team of talented engineers.
- Expertise with various ETL technologies and familiar with ETL tools.
- You have engineered metrics and statistical information out of massive and complex datasets (e.g. Hive, Spark MLlib, Druid, Solr, Kafka).
- You are proficient in at least one programming language (e.g. Python, Scala) and are comfortable developing code within a team environment (e.g. git, testing, code reviews).
- You have built robust data and analytic pipelines and have a keen eye for where to automate (e.g. Oozie, Airflow).
- Have solid understanding of both relational and NoSQL database technologies.
- Experience with visualization, data mining, or statistical tools
- Data architecture skills
The ideal candidate will have outstanding communication skills, proven data infrastructure design and implementation capabilities, strong business acumen, and an innate drive to deliver results. He/she will be a self-starter, comfortable with ambiguity and will enjoy working in a fast-paced dynamic environment. Responsibilities will include - Establish the processes needed to achieve operational excellence in all areas, including project management and system reliability - You will build a high-quality BI and Data Warehousing team - Build relationships with Data Scientists, Product Managers and Software Engineers to understand data needs - Manage data pipeline availability and reliability - Has a keen focus on engineering excellence and data quality - Manage the hardening and launching of new data models and data pipelines in production - Lead development of data tools to support analysis and data resources to support new product launches - Drive data quality across the product vertical and related business areas - Manage the delivery of insightful dashboards and data visualizations - Establish SLA’s for all data sets and processes running in production - You will report to the Head of Siri Data Analytics - Excellent writing and interpersonal skills - Thorough knowledge of macOS and iOS is helpful - Ability to stay focused and prioritize a heavy workload while achieving exceptional quality - You are upbeat, adaptable, and results-oriented with a positive attitude
Education & Experience
B.S., M.S., or PhD in Computer Science, Computer Engineering, or equivalent practical experience
- Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.