Job Description

The Group You\'ll Be A Part Of The Group You\'ll Be A Part OfMicron Global Account Equipment Intelligence OrganizationThe Impact You\'ll MakeThe Equipment Intelligence Engineer will provide remote response (Telit) and on-site advanced service software (Ambari, Banana, Hadoop, Solr, Kafka etc.) to manage, troubleshoot, analyze, and support Micron EI-DH & EI-DA data infrastructure. Identified personnel will be Data Science Specialist supporting Deposition products, as well as site Technical Leader for Equipment Intelligence.The goal is to meet customer digital specifications and digital scorecard requirements for high-volume production analysis and troubleshooting, ensuring Lam Business Performance is maintained.What You\'ll Do

• Remote & In-Site Data Management

• Utilize remote response tools (Telit) and advanced service software (Ambari, Banana, Hadoop, Solr, Kafka, etc.) to manage customer data infrastructure.
• Ensure alignment with customer digital specifications and scorecards for optimum production performance.
• Performance Analysis & Troubleshooting

• Conduct high-volume production analysis and troubleshooting to ensure optimal performance on Lam EI-DH & EI-DA server infrastructure.
• Support Lam Business Performance by addressing data ingestion and analysis issues promptly.
• Collaboration & Escalation Management

• Partner with CSBG GPS/RPS, Account Team, and Micron SMAl to resolve critical escalations and issues.
• Provide speedy solutions for data ingestion and analysis challenges.
• Data Science Analysis (DPG Products)

• Receive training and equip with Lam Equipment Intelligence capabilities, including EI-DA, El-App, Jupyter Notebook (Python Coding), and JMP analytics.
• Collaborate with DPG El experts to support Lam Deposition Products notebook deployment, creation, and analysis.
• Actively use Lam El software to meet site install base performance and Lam commitments, securing future business and customer confidence.
• Site Equipment Intelligence Specialist

• Lead and coach site Account Team field engineers in the proactive and proficient use of Lam El software.
• Employ various analytical approaches to enhance performance, efficiency in speed to solution.

Who We\'re Looking ForMinimum Qualifications:

• Bachelor\'s degree in Computer Science, Data Science, Engineering, or a related field

Preferred Qualifications

• At least three years of experience within the semiconductor or related field is preferred.
• Proven track record of managing and troubleshooting data infrastructure (Hadoop, Solr, Kafka, etc.).
• Proficiency in Python coding and experience with Jupyter Notebook.
• Strong analytical skills and experience with JMP analytics.
• Previous work analyzing multi-dimensional data, including segmentation, reconstruction, classification, or manipulation is a big plus.
• Excellent communication and collaboration skills.

Our CommitmentWe believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company\'s intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. \'On-site Flex\' you\'ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. \'Virtual Flex\' you\'ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.

Lam Research