Internship/Co-Op: Data Engineer

Location: San Diego, CA, USA

Co-Op: Data Engineer

Organization: IT & Data, Chief Data Office US Location: United States, hybrid Employment Type: College Co-Op

Job Mission

As a Data Engineer Co-Op at ASML, you will help develop data pipelines and data products that transform laser-machine and enterprise data into trusted, usable information.

Working with experienced data engineers, data architects, IT specialists, and business stakeholders, you will contribute to technical solutions that support product capabilities, analytics, AI, system performance, and ultimately customer satisfaction.

This role provides an opportunity to work with complex, high-value data in a collaborative engineering environment while learning how modern data solutions are designed, tested, deployed, documented, and operated at enterprise scale.

Job Description

As a member of the CDO US team, you will

Develop and enhance data pipeline solutions that contribute to product features, technical roadmaps, analytics, and AI use cases.

Build data ingestion, transformation, validation, and integration processes for laser-machine and enterprise data.

Contribute to automated continuous data integration pipelines used to build, test, and release data solutions.

Develop and optimize SQL transformations, data models, and analytical datasets.

Apply systematic problem-solving to identify root causes, resolve technical issues, and standardize reusable solutions.

Collaborate with cross-functional engineering and business teams on system design changes and improvements to system performance.

Work with business users to understand requirements and translate business goals into feasible technical solutions.

Collaborate with data architects, software engineers, AI engineers, and IT team members to achieve shared project goals.

Help improve data quality, observability, monitoring, lineage, and governance.

Apply industry practices for code quality, automated testing, version control, maintainability, and technical documentation.

Refactor and improve existing code so that legacy and modern systems can coexist during technology transitions.

Participate in code reviews, technical design discussions, agile delivery activities, and continuous improvement.

Document data pipelines, interfaces, data models, decisions, dependencies, and operating procedures.

Contribute reusable data components and engineering patterns that can support multiple teams and use cases.

Education and Experience

Must be pursuing a Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Data Engineering, Information Systems, Software Engineering, or a related field.

Knowledge of or experience with Python, SQL, Java, or a comparable programming language.

Knowledge of relational databases, data modeling, and data integration concepts.

Familiarity with Databricks, SQL Server, or other database and data-platform technologies.

Familiarity with Microsoft Azure or another cloud environment.

Exposure to ETL/ELT development, data pipelines, or analytical data processing.

Academic, personal, or professional project experience performing data engineering or similar work.

Familiarity with Git, automated testing, CI/CD, or modern software-development practices is preferred.

Experience with data quality, pipeline monitoring, or data visualization is a plus.

Skills and Competencies

Strong customer focus and a commitment to customer satisfaction through quality, prioritization, efficiency, and professionalism.

Strong numerical, analytical, and structured problem-solving skills.

Ability to decompose complex problems, clarify requirements, and propose feasible solutions.

Attention to detail and the ability to complete assignments with a high degree of accuracy.

Ownership and accountability for assigned work, including raising risks and following through on commitments.

Ability to perform effectively in a demanding environment with changing priorities and workloads.

Open, clear, concise, and professional communication.

Ability to establish cooperative working relationships with colleagues, technical teams, and business stakeholders.

Willingness to seek feedback, learn new technologies, and continuously improve.

Understanding of the importance of code health, testing, maintainability, and documentation.

Ability to balance immediate delivery needs with the development of scalable and reusable solutions.

What Success Looks Like

During the co-op, you will have the opportunity to

Deliver working data pipelines, transformations, or data products that contribute to real business or engineering outcomes.

Improve the quality, reliability, accessibility, or maintainability of data used by internal teams.

Demonstrate disciplined engineering through testing, documentation, code reviews, and version control.

Translate a defined business or engineering need into a practical technical solution.

Collaborate effectively across data, IT, engineering, analytics, and AI teams.

Develop reusable solutions rather than addressing each technical problem in isolation.

Build practical experience with enterprise data platforms, cloud technology, and production-oriented engineering.

Team Culture

The CDO US team works across organizational and technical boundaries to turn data into scalable business and engineering value. We are looking for a student who:

Is curious about how data supports advanced engineering, analytics, AI, and customer outcomes.

Takes ownership while remaining comfortable asking questions and seeking guidance.

Approaches problems systematically and looks for root causes, not only immediate fixes.

Values collaboration over individual heroics.

Communicates openly about progress, risks, dependencies, and lessons learned.

Cares about data quality, code quality, documentation, and long-term maintainability.

Can adapt as priorities change without losing focus on quality and delivery.

Looks for opportunities to standardize, automate