Job Description

Job Description:
The Intel Foundry Manufacturing and Supply chain FMSC Automation team is looking for a highly motivated Big Data Engineer with strong data engineering skills for data integration of various manufacturing data. You will be responsible for engaging with customers and driving development from ideation to deployment and beyond. This position is a technical role that requires the direct design and development of robust, scalable, performant systems for world-class manufacturing data engineering.
Responsibilities include:
� Create and maintain optimal data architecture
� Assemble large, complex data sets that meet functional and non-functional business requirements
� Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
� Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources
� Work with stakeholders including the users, cross functional teams to assist with data-related technical issues and support their data infrastructure needs.
� Standard process to keep data secure with right access and authorization
� Focus on automated testing and robust monitoring
The ideal candidate must exhibit the following behavioral traits:
� Excellent problem solving and interpersonal communication skills
� Strong desire to learn and share knowledge with others.
� Be inquisitive, innovative, and a team player with a strong focus on quality workmanship.
� Troubleshooting skills and root cause analysis for performance issues
� Ability to lean, adopt and implement new skills to drive innovation and excellence.
� Ability to work with cross functional teams in dynamic environment

Qualifications

Minimum Qualifications:
� A bachelor's with 5+ years of experience in CS/CE or a related field
� Experience building and optimizing big data pipelines
� Experience with skills pf handling unstructured data
� Experience with data transformations, structures, metadata, workload management
� Experience with big data tools: Spark, Kafka, NIFI, etc.
� Experience with at least programming languages: Python, C#, .NET
� Experience with relational SQL and NOSQL DBs
� Experience in leveraging open-source packages
� Experience in cloud native skills such as Docker, Kubernetes, Rancher etc.
Good to have skills:
� Experience with semiconductor manufacturing
� Experience of data engineering on cloud
� Experience in developing AI/ML Solutions

Inside this 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.

Benefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here.

Working Model

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. In certain circumstances the work model may change to accommodate business needs.