Lead Engineer- Data/Machine Learning
Santa Clara Valley (Cupertino), California, United States
Software and Services
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple, and help us leave the world better than we found it! Apple is seeking a proven Engineer to join the Manufacturing Systems and Infrastructure Data Quality Management team. Apple is a data-centric company where many critical decisions are made based on data. The completeness, accuracy and timeliness of data has huge implications to our decision- making. Every shipped Apple product undergoes rigorous testing at our factories to ensure the best customer experience. The MSI team handles the data collection, data governance and reporting of all manufacturing assembly and test data. The Product Operations team is looking for an extraordinary and solutions-oriented engineer to join our team. You will help design and implement our data governance and data quality strategy and tools to the substantial iPhone and other Apple products supply chain data and help build the strong data foundations for the future of our manufacturing systems and smarter factories. We will be collaborating and working with multi-functional teams across Apple and applying data best practices and standards to large-scale data.
- 7+ years of development and/or system integration experience
- Polyglot programmer with proficiency in Python and any of JVM-based languages, skilled in problem-solving and software development
- Working experience in designing and developing end to end data solutions
- Proficiency working with large datasets, cloud database platforms and SQL.
- Working experience in but not limited to Hadoop, Spark/PySpark, Hive, Kafka and NoSQL databases a plus.
- Experience in applying ML techniques in manufacturing and testing space is a major plus.
- Knowledge of data mining, statistical modeling, and machine learning methodologies.
- Experience articulating and translating business questions and using statistical techniques to arrive at an answer using available data.
- Experience with data visualization and presentation, familiar with data analysis tools such as Tableau, JMP.
- Strong facilitation skills (requirements sessions, design meetings, progress and status meetings)
A demonstrated passion for solving large data problems using big data technologies, such Spark, Kafka, and NoSQL based solution. Strong analytical product intuition and ability to use data impact fully in guiding development of data quality tools, process and data consumer experiences. Lead evaluation and implmentation of large datasets across various data quality dimensions and propose technical and process guidelines and solutions. Partner and understand business data quality needs from operations data owners and stakeholders, define data quality metrics and establish an enterprise view of data quality to bring focus and attention to highest priority data issues. Perform investigations to enrich our understanding of how people use data across product operations teams and help define data quality KPIs and enterprise data quality platform. Build and run cross-functional data quality initiatives, processes and adoption of data best practices and standards. Ability to manage complex relationships across multiple functions and establish positive relationships. Outstanding communication and presentation skills, written and verbal, to all levels of an organization.
Education & Experience
Bachelor’s degree in an engineering related field, or equivalent experience
- Apple is an Equal Opportunity Employer that is committed to inclusion and diversity. We also take affirmative action to offer employment and advancement opportunities to all applicants, including minorities, women, protected veterans, and individuals with disabilities. Apple will not discriminate or retaliate against applicants who inquire about, disclose, or discuss their compensation or that of other applicants