Data Engineer Co-op: Build Enterprise Data Pipelines

ASML; San Diego (CA); Hybrid; USD 30,000 - 47,000; Part time

Job summary

ASML’s Chief Data Office US is seeking a Data Engineer Co-Op in the United States with hybrid work. You will help develop data pipelines and products, transforming laser-machine and enterprise data into trusted information.

You will collaborate with data engineers, architects, IT, and business stakeholders to deliver scalable data solutions in an enterprise setting. The role emphasizes pipeline development, SQL optimization, data quality, and documentation, with opportunities to learn

Qualifications

• Pursuing a Bachelor’s or Master’s degree in a relevant field.
• Experience with Python, SQL, Java, or similar languages.
• Familiarity with Databricks, SQL Server, or other data platforms.
• Knowledge of cloud environments such as Microsoft Azure.
• Exposure to ETL/ELT development and data pipelines is a plus.

Responsibilities

• Develop and enhance data pipelines and data products.
• Build ingestion, transformation, validation, and integration processes.
• Contribute to automated data integration pipelines for CI/CD.
• Develop and optimize SQL transformations and analytical datasets.
• Collaborate with cross-functional teams on system design and performance.
• Document data pipelines, models, and operating procedures.
• Participate in code reviews, agile delivery, and continuous improvement.

Skills

Python

SQL

Java

Data pipelines

Git

CI/CD

Data quality

Data modeling

Analytical thinking

Problem-solving

Education

Bachelor’s or Master’s degree in Computer Science / Computer Engineering / Data Engineering / Information Systems / Software Engineering

Tools

Databricks

SQL Server

Azure

ETL/ELT tools

Job description

ASML’s Chief Data Office US is seeking a Data Engineer Co-Op in the United States with hybrid work. You will help develop data pipelines and products, transforming laser-machine and enterprise data into trusted information.

You will collaborate with data engineers, architects, IT, and business stakeholders to deliver scalable data solutions in an enterprise setting. The role emphasizes pipeline development, SQL optimization, data quality, and documentation, with opportunities to learn