DTCO Systems Analysis Engineer

Intel Corporation•Austin, TX

4d•Onsite

About The Position

As a Data Analyst at Intel, you will play a pivotal role in enabling smarter technological decisions by leveraging advanced data analysis techniques to drive program and project success. You will act as the critical link between foundry and customer engineering teams, transforming design PPA data into actionable insights, technical specifications, and data-driven asks from foundry technology teams. Your work will directly impact Intel's ability to predict technology trends, improve foundry design performance, and innovate in a rapidly evolving industry. By applying mathematical and statistical expertise and collaborating closely with cross-functional teams, you will help shape the future of data-driven decision-making and contribute to Intel's mission of delivering world-class foundry technology solutions.

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, or a related STEM field.
1+ years of experience in data analysis with a Bachelor's degree
6+ months of experience in data analysis tools and techniques such as SAS, SAP, SQL, or Python.
3+ months in data validation, cleansing, and/or verification methodologies.
3+ months using reporting tools to generate dashboards and visualizations.

Nice To Haves

Master's degree in a relevant STEM field.
Strong mathematical and statistical analysis skills with the ability to interpret complex datasets.
Familiarity with automation tools for analytics and reporting.
Experience collaborating with cross-functional teams in a fast-paced, technical environment.
Exceptional problem-solving skills and adaptability to ambiguous challenges.
A passion for discovering insights that drive impactful business outcomes.

Responsibilities

Extract, process, and cleanse complex design datasets to ensure data integrity and accuracy.
Identify, analyze, and interpret patterns and trends in large design reports and datasets using statistical and predictive modeling techniques.
Develop and automate data analytics, validation, and reporting tools to streamline processes and increase efficiency.
Act as a liaison between foundry tech and customer engineering teams, gathering and translating design requirements into technical specifications for foundry.
Monitor data integration performance and quality control plans, suggesting improvements to enhance accuracy and efficiency.
Develop interactive and intuitive reports.