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.

Requisition ID:

78258

Job Description:

Description 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. Responsibilities What you will work on

Develop and maintain data ingestion and transformation pipelines using Python, SQL, PySpark, and Databricks notebooks.

\nUse Databricks Workflows and jobs to orchestrate, schedule, monitor, and troubleshoot data processing activities.\nBuild and test ETL/ELT solutions for structured and semi-structured data from enterprise systems, databases, files, and APIs.\nWork with Delta Lake and lakehouse concepts, including Bronze, Silver, and Gold data layers.\nApply data profiling, validation, reconciliation, and quality checks to improve data reliability.\nAssist with onboarding new datasets into Azure Data Lake Storage and Databricks.\nSupport pipeline monitoring, root-cause analysis, defect resolution, and documentation.\nUse Git and CI/CD practices for version control, peer review, testing, and controlled deployments.\nCollaborate with data engineers, analysts, platform teams, and business stakeholders to understand requirements and deliver usable data products. Databricks Learning Focus 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. What You Could Learn Databricks & Spark

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

Required Experience and Skills 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.\nAbility to work on-site for 3 month internship period\nBasic programming proficiency in Python and the ability to write clear, testable code.\nWorking knowledge of SQL, relational databases, joins, aggregations, and data manipulation.\nUnderstanding of data structures, algorithms, and software engineering fundamentals.\nStrong analytical and problem-solving skills with attention to detail.\nClear written and verbal communication skills, with the ability to collaborate in a team environment.\nCuriosity, accountability, and willingness to learn new technologies. Desired Experience and Skills Academic, internship, or personal project experience with Databricks, Apache Spark, or PySpark.\nExposure to Microsoft Azure, Azure Data Factory, Azure Data Lake Storage, or Azure SQL.\nUnderstanding of ETL/ELT, data warehousing, lakehouse, or medallion architecture concepts.\nFamiliarity with Git, Azure DevOps, CI/CD, Linux, REST APIs, or Power BI.\nAwareness of data governance, security, access control, or data quality principles.\nDatabricks or Microsoft Azure learning credentials are an advantage but not required. Ideal Candidate Profile Takes ownership of assigned work and communicates progress or blockers early.\nApproaches problems methodically and validates results before considering work complete.\nCan learn independently while seeking guidance at the right time.\nValues clean code, documentation, data security, and reliable delivery.\nIs interested in building a long-term career in data engineering and cloud data platforms. The typical pay range for an Engineering intern across the U.S. is currently USD $26.00

$47.50 per hour and for a Non-Engineering intern across the U.S. is currently USD $22.50
$42.

00 per hour. Starting pay will depend on level of education, the ultimate job duties and requirements, and work location. Skyworks has different pay ranges for different work locations in the U.S. Skyworks is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

Skyworks strives to create an accessible workplace; if you need an accommodation due to a disability, please contact us at accommodations@skyworksinc.com. 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