Data Engineer, Staff (Semiconductor Engineering)

About the role

The Staff Data Engineer will lead the design and implementation of scalable data platforms that enable semiconductor engineering insights. You will work with Test, Product, Yield and NPI teams to turn high‑volume test data into reusable data products and analytics solutions.

Key responsibilities

• Design, develop and optimise end‑to‑end data products and ETL/ELT pipelines for wafer sort, final test, parametric, quality and manufacturing data.
• Translate business requirements into cloud‑native architectures that support high‑velocity ingestion, transformation, semantic modelling and analytics consumption.
• Implement business logic for yield analysis, binning, parametric trend monitoring, failure analysis and test program optimisation.
• Establish data governance frameworks, including glossaries, data dictionaries, metadata, lineage, quality controls and access management.
• Continuously improve platform scalability, performance and reliability using cloud data‑engineering best practices.

Required profile

• 8‑15 years of experience in Data Engineering or Data Platform Engineering.
• Strong hands‑on experience with cloud data platforms, preferably AWS.
• Proficiency in Python (including PySpark and Pandas) and SQL for data modelling, optimisation and performance tuning.
• Experience delivering end‑to‑end data solutions across the full data lifecycle.

Required skills

• Python
• PySpark
• Pandas
• SQL
• AWS
• Cloud data platforms
• ETL/ELT design
• Data modelling
• Data governance
• Metadata management