Job description

Who We Are Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world. What We Offer Salary: $140,500.00 - $193,000.00 Location: Santa Clara,CA You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more. At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits . Key Responsibilities • Partner with process engineers, and integration teams to understand wafer experiment workflows—including etch, deposition, and metrology steps—and translate experimental and yield-learning objectives into actionable data and reporting requirements. • Design, develop, and maintain metrics, dashboards, and analytical reports focused on process tool performance, recipe execution, chamber health, and wafer-level traceability, and using ClickHouse, SQL, and Python. • Write detailed specifications for new data pipelines to onboard additional metrology tools, sensors, or process data sources, collaborating with data engineering to ensure proper schema design, transformations, and quality checks within the AWS/Kafka/ClickHouse stack. • Validate and reconcile data from disparate systems (MES, tool logs, recipe management, metrology platforms, yield databases) to ensure accurate linkage at the wafer, lot, run, and step level within the technical data warehouse. • Develop reusable Python scripts and SQL queries for ad-hoc and recurring analyses such as DOE evaluation, process window characterization, virtual metrology exploration, and wafer-to-wafer or lot-to-lot comparisons. • Work within established data governance and access controls to ensure accuracy, timeliness, and appropriate confidentiality of all engineering reports, dashboards, and experimental data. • Create and maintain documentation for datasets, table schemas, KPIs, and pipeline logic—including data lineage, business definitions, and usage examples tailored to process contexts. • Train and support application developers and data analysts in using the data warehouse, BI tools, and self-service dashboards; gather feedback to continuously improve data products and user experience. • Collaborate with data scientists and ML engineers to operationalize predictive models by ensuring required features and labels are available, accurate, and well-documented in the warehouse. • Create automated workflows for data ingestion, cleansing, and integration of large-scale process and metrology datasets, leveraging Python, ETL orchestration tools, and cloud services on AWS. • Assess evolving reporting needs in the context of R&D priorities and technology roadmaps; propose and deliver appropriate solutions ranging from quick ad-hoc analyses to production-grade dashboards. • Generate internal documentation, presentations, and technical reports summarizing experimental results, data quality assessments, and analytics insights for cross-functional stakeholders. Required Skills and Knowledge • Ability to translate engineering workflows and business needs into data requirements and specifications. • Experience working directly with engineers, operations teams, or technical stakeholders. • Solid documentation, communication, and stakeholder engagement skills. • Experience designing and validating metrics, KPIs, and dashboards for operational or engineering environments. • Strong proficiency in SQL and Python for data analysis, automation, and pipeline support. • Experience with BI and visualization tools (Tableau, Power BI, Superset, Grafana, Looker, or similar). • Version control (Git), CI/CD for analytics, and data documentation tooling. Qualifications • Bachelor’s degree in data science, computer science, engineering, or related field. • 4+ years of experience in data analysis, preferably within a high-tech or manufacturing environment. • Demonstrated experience supporting business units with analytical solutions. Preferred Attributes • Strong attention to detail and organizational skills. • Excellent communication skills for presenting complex findings to stakeholders. • Ability to work independently and collaboratively in a fast-paced environment. • Proactive approach to process improvement and automation. • Software Development Process • JIRA, BitBucket Functional Knowledge • Demonstrates depth and/or breadth of expertise in own specialized discipline or field Business Expertise • Interprets internal/external business challenges and recommends best practices to improve products, processes or services Leadership • May lead functional teams or projects with moderate resource requirements, risk, and/or complexity Problem Solving • Leads others to solve complex problems; uses sophisticated analytical thought to exercise judgment and identify innovative solutions Impact • Impacts the achievement of customer, operational, project or service objectives; work is guided by functional policies Interpersonal Skills • Communicates difficult concepts and negotiates with others to adopt a different point of view Additional Information Time Type: Full time Employee Type: Assignee / Regular Travel: Yes, 10% of the Time Relocation Eligible: No The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable. For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement. Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law. In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.

Requirements

Must-haves

Santa Clara,CA
Design, develop, and maintain metrics, dashboards, and analytical reports focused on process tool performance, recipe execution, chamber health, and wafer-level traceability, and using ClickHouse, SQL, and Python.
Develop reusable Python scripts and SQL queries for ad-hoc and recurring analyses such as DOE evaluation, process window characterization, virtual metrology exploration, and wafer-to-wafer or lot-to-lot comparisons.
Work within established data governance and access controls to ensure accuracy, timeliness, and appropriate confidentiality of all engineering reports, dashboards, and experimental data.
Create and maintain documentation for datasets, table schemas, KPIs, and pipeline logic—including data lineage, business definitions, and usage examples tailored to process contexts.
Train and support application developers and data analysts in using the data warehouse, BI tools, and self-service dashboards; gather feedback to continuously improve data products and user experience.
Collaborate with data scientists and ML engineers to operationalize predictive models by ensuring required features and labels are available, accurate, and well-documented in the warehouse.
Create automated workflows for data ingestion, cleansing, and integration of large-scale process and metrology datasets, leveraging Python, ETL orchestration tools, and cloud services on AWS.
Assess evolving reporting needs in the context of R&D priorities and technology roadmaps; propose and deliver appropriate solutions ranging from quick ad-hoc analyses to production-grade dashboards.
Generate internal documentation, presentations, and technical reports summarizing experimental results, data quality assessments, and analytics insights for cross-functional stakeholders.
Required Skills and Knowledge
Ability to translate engineering workflows and business needs into data requirements and specifications.
Experience working directly with engineers, operations teams, or technical stakeholders.
Solid documentation, communication, and stakeholder engagement skills.
Experience designing and validating metrics, KPIs, and dashboards for operational or engineering environments.
Strong proficiency in SQL and Python for data analysis, automation, and pipeline support.
Experience with BI and visualization tools (Tableau, Power BI, Superset, Grafana, Looker, or similar).
Version control (Git), CI/CD for analytics, and data documentation tooling.
Bachelor’s degree in data science, computer science, engineering, or related field.
4+ years of experience in data analysis, preferably within a high-tech or manufacturing environment.
Demonstrated experience supporting business units with analytical solutions.
Strong attention to detail and organizational skills.
Excellent communication skills for presenting complex findings to stakeholders.

Nice-to-haves

Preferred Attributes

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigosqlpythonawsmlci/cdjiraaccessibility

Platform: eightfold
Effort: medium