Data Application Engineer

Do you love crafting elegant solutions to highly complex challenges. Do you intrinsically see the importance in every detail. As part of our Silicon Technologies group, you'll help design and manufacture our next-generation, high-performance, power-efficient processor, system-on-chip (SoC). You'll ensure Apple products and services can seamlessly and expertly handle the tasks that make them beloved by millions. Joining this group means you'll be responsible for crafting and building the technology that fuels Apple's devices. Together, you and your team will enable our customers to do all the things they love with their devices. At Apple, innovative concepts swiftly transform into groundbreaking products, services, and customer experiences. By cultivating passion and unwavering dedication, the potential for extraordinary accomplishments becomes limitless. Apple Silicon is seeking an individual to deliver data-driven insights to develop the next Apple products. We are seeking an individual to assist us in creating, sustaining, and improving our data analytics infrastructure. This includes setting up data pipelines, performing data analysis, and developing dashboards to visualize data. The engineer will provide insights by providing product performance reports, statistical and machine learning analysis, and model development.

Description Be a domain expert in data usage, availability, and structure. Set up product performance tracking and reporting. Improve and enhance the database, data pipeline, and develop and enhance dashboards to visualize and provide insights. Provide analysis and insights of the semiconductor product performance. Collaborate with semiconductor product and test engineering teams to understand data needs and develop data delivery solutions. Work with infrastructure teams, including database administrators and database developers, to ensure the proper functioning of all data pipelines and the health of the data warehouse.

Responsibilities

• Design and implement comprehensive product analysis frameworks for semiconductor test and manufacturing data.
• Design and implement anomaly detection to improve product quality and prevent defects.
• Perform statistical analysis and machine learning modeling to identify yield limiters and process improvement opportunities.
• Create and enhance interactive Tableau dashboards and visualizations to communicate trends and insights.
• Administer and optimize Yield Management Systems to ensure data integrity and system performance.
• Collaborate with cross-functional teams, including product engineering, test engineering, and manufacturing, to drive product improvements.

Minimum Qualifications

• Bachelors Degree plus 3 years of relevant experience
• (Degree in EE, MSE, ChemE, Statistic, Physics, or related)

Preferred Qualifications

• Strong proficiency in large datasets processing, extraction, analysis, and reporting
• Experience in yield analysis, defect reduction, and process improvement
• Proficiency in SQL database query and creating curated datasets
• Proficiency in Python programming language
• Strong proficiency in creating Tableau dashboards and workflows
• Proven track record of taking ownership and successfully delivering results
• Ability to learn new technologies and approaches
• Strong analytical and problem-solving skills
• Experience with Linux operating systems
• In-depth knowledge of the semiconductor process, test, and manufacturing flow
• Strong proficiency in statistical and machine learning analysis and model development within the high-tech manufacturing and test environment
• Experience in Yield Management System administration
• Experience with STDF (Standard Test Data Format) handling and analysis
• Experience with version control systems (Git) and software development best practices
• Background in Six Sigma or other process improvement methodologies

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote 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. Learn more about your EEO rights as an applicant .