Data Engineering Summer Intern

Job Title:

Data Engineering Summer Intern (May-Aug '27)

Posting

Start Date:

8/25/26

Job Location(s):
Irvine

If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high-performance analog semiconductors whose solutions are powering the wireless networking revolution.

Through our broad technology expertise and one of the most extensive product portfolios in the industry, we are Connecting Everyone and Everything, All the Time.

At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management, and the freedom to make meaningful contributions in a setting that encourages creative thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together are changing the way the world communicates.

We are looking for a motivated Student Engineer to join our Enterprise Systems and Data Engineering team. You will work with experienced engineers to build, enhance, test, and support modern data solutions using Databricks and Microsoft Azure. The internship offers practical exposure to enterprise-scale data pipelines, data quality, cloud storage, governance, and production engineering practices.

This summer internship period is from May/June to August/September 2027.

What you will work on -

• Develop and maintain data ingestion and transformation pipelines using Python, SQL, PySpark, and Databricks notebooks.
• Use Databricks Workflows and jobs to orchestrate, schedule, monitor, and troubleshoot data processing activities.
• Build and test ETL/ELT solutions for structured and semi-structured data from enterprise systems, databases, files, and APIs.
• Work with Delta Lake and lakehouse concepts, including Bronze, Silver, and Gold data layers.
• Apply data profiling, validation, reconciliation, and quality checks to improve data reliability.
• Assist with onboarding new datasets into Azure Data Lake Storage and Databricks.
• Support pipeline monitoring, root-cause analysis, defect resolution, and documentation.
• Use Git and CI/CD practices for version control, peer review, testing, and controlled deployments.
• Collaborate with data engineers, analysts, platform teams, and business stakeholders to understand requirements and deliver usable data products.

• Hands-on exposure may include:
  Databricks workspace and notebooks, Apache Spark and PySpark, Delta Lake, Databricks Workflows, SQL Warehouses, Unity Catalog fundamentals, data quality controls, performance basics, and lakehouse architecture.

• Databricks & Spark
  - Develop notebooks and scalable transformations with SQL, Python, and PySpark.
• Pipeline Engineering
  - Understand ingestion, orchestration, testing, monitoring, and operational support.
• Cloud Data Platforms
  - Work with Azure-based storage, integration, and data processing patterns.
• Data Quality & Governance
  - Apply validation, documentation, access control, lineage, and reliability practices.
• Engineering Delivery
  - Gain experience with Git, code reviews, CI/CD, Agile delivery, and stakeholder collaboration.

• Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Information Technology, Data Science, Electronics Engineering, or a related technical discipline.
• Ability to work on-site for 3 month internship period
• Basic programming proficiency in Python and the ability to write clear, testable code.
• Working knowledge of SQL, relational databases, joins, aggregations, and data manipulation.
• Understanding of data structures, algorithms, and software engineering fundamentals.
• Strong analytical and problem-solving skills with attention to detail.
• Clear written and verbal communication skills, with the ability to collaborate in a team environment.
• Curiosity, accountability, and willingness to learn new technologies.

• Academic, internship, or personal project experience with Databricks, Apache Spark, or PySpark.
• Exposure to Microsoft Azure, Azure Data Factory, Azure Data Lake Storage, or Azure…