Module Engineer - Dry Etch

Job Details:

Job Description: 

Dry Etch group under Intel's Technology Development organization is seeking a skilled and motivated process engineer with emphasis on data analysis to support semiconductor manufacturing research and development processes for our U.S.-based operations.

• The ideal candidate will have a strong background in data analytics, a solid understanding of semiconductor manufacturing, and the ability to work collaboratively across time zones. This position requires advanced problem-solving skills, technical expertise, and experience in data-driven decision-making to optimize manufacturing performance.

Key Responsibilities:

• Analyze manufacturing process data to identify trends, anomalies, and improvement opportunities.
• Develop dashboards and reports for real-time monitoring and decision-making support for U.S.-based teams.
• Collaborate with U.S. semiconductor manufacturing teams to understand process requirements and implement data solutions.
• Utilize advanced statistical methods, machine learning, and predictive modeling to enhance yield, reduce defects, and optimize production.
• Ensure data integrity, accuracy, and security in all analyses and reporting.
• Support root cause analysis for process issues using data-driven methodologies.
• Maintain and improve data pipelines for automated data processing and reporting.
• Coordinate with cross-functional teams (engineering, operations, and IT) to deliver.

Qualifications:

Minimum Qualifications
Master’s degree or Bachelor’s  in electrical engineering, Computer Science, Mechanical Engineering, Chemical Engineering, Computer Engineering, Applied Mathematics, or other relevant related degrees with Industry experience in one of the following:

• B.Tech with 5+ years and M.Tech with 2+ years of experience in data analytics, preferably in a manufacturing or semiconductor environment.
• Strong understanding of statistical analysis, machine learning models, and process control methodologies.
   

Preferred Qualifications:

• Proficiency in data analysis tools and programming languages: Python, R, SQL, etc.
• Experience with visualization tools such as Tableau, Power BI, or equivalent.
• Knowledge of semiconductor manufacturing processes and yield analysis is highly preferred.
• Excellent problem-solving and analytical skills with a keen eye for detail.
• Strong communication and collaboration skills to work with global teams.
• Ability to manage multiple priorities in a fast-paced environment.
   
• Working Hours:
• The position will primarily align with local time, with some flexibility to accommodate collaboration across U.S. time zones.

          

Job Type:

Experienced Hire

Shift:

Shift 1 (India)

Primary Location: 

India, Bangalore

Additional Locations:

Business group:

As the world's largest chip manufacturer, Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support.  Employees in the Technology Development and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore’s Law to bring smart, connected devices to every person on Earth.

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.