Data Engineer DevOps
Summary
Build and optimize data pipelines for semiconductor manufacturing using AWS, PySpark, Redshift, and Python to support analytics and AI initiatives across global fabs.
About GlobalFoundries GlobalFoundries is a leading full-service semiconductor foundry providing a unique combination of design, development, and fabrication services to some of the world's most inspired technology companies. With a global manufacturing footprint spanning three continents, GlobalFoundries makes possible the technologies and systems that transform industries and give customers the power to shape their markets. For more information, visit Your work will have a direct impact in our expanding Fab Operations, in building out our platforms of purpose-built technologies such as smart mobile devices, personal computing, home and industrial IoT, automotive and more. You will have access to the latest technological developments at GF Labs, with opportunities for patent submissions, presenting your ideas on a global platform, and enjoy GF-wide collaboration across our fabs and offices around the world. Introduction of the Department The Data Analytics & AI Enablement Group is responsible for integrating corporate application, manufacturing and engineering data out of a high variety of source systems used in the semiconductor engineering and production process. The data warehouse solutions are used in the GLOBALFOUNDRIES Fabs in Dresden, in the US and in Singapore, and the Data Analytics & AI Enablement Group is responsible to conceptualize and provide timely, high-quality solutions that address analysis needs of engineers in a leading-edge semiconductor foundry. What You Will Do
- Assist in understanding the business case and contribute to translating it into a technical solution involving AWS Cloud Services, PySpark, EMR, Python, and Cloud DB Redshift / Postgres.
- Learn and assist with PL/SQL development for high-volume datasets.
- Support the preparation of data warehouse design artifacts based on given requirements (ETL framework design, data modeling, source-target-mapping), and assist with DB query monitoring for tuning and optimization opportunities.
- Demonstrated academic or project-based experience with complex database projects and high-volume data environments.
- Possess foundational problem-solving skills; familiarity with various root cause analysis methods; and the ability to document identified problems and determined resolutions.
- Contribute ideas and recommendations regarding enhancements and/or improvements to existing systems.
- Learn to provide appropriate input on database management standards and assist with monitoring transaction activity and utilization.
- Assist with performance issues analysis and tuning.
- Contribute to data warehouse design and development, including logical and physical schema design.
- Bachelor's Degree in Computer Science
- Demonstration of project management skills, the ability to innovate and execute solutions that matter; the ability to navigate ambiguity.
- Profiles with prior internship/project experience in the relevant field will be an advantage
- Able to work independently, with good communication skills and effective teamwork
- Familiarity with or academic exposure to AWS Services, Big Data concepts, PySpark, Python, and Cloud DB Redshift.
- Data Warehousing Concepts: Foundational knowledge of data warehouse architecture, trends, and design approaches, including Dimensional Modeling and ERD design.
- Documentation and Flow Mapping: Strong conceptual understanding with solid technical documentation skills, particularly the ability to document data flows within business processes.
