Data Engineering Summer/Fall Co-Op (June - Dec '27)

Skyworks Solutions, Inc.; Irvine (CA); On-site; USD 36,000 - 66,000; Full time

Job summary

Skyworks Solutions, Inc. in Irvine invites a Data Engineering Intern for a Summer/Fall Co-Op (June–Dec 2027). You will help build modern data pipelines with Python, SQL, PySpark, and Databricks, and gain exposure to Azure storage, data governance, and CI/CD practices.

This on-site internship emphasizes hands-on learning and collaboration with cross-functional teams. You will work with Databricks notebooks, Delta Lake concepts, and lakehouse architecture while contributing to production-quality

Qualifications

• Currently pursuing or recently completed a Bachelor’s or Master’s degree in a technical field.
• Ability to work on-site 5 days per week.
• Proficiency in Python; familiarity with HTML and JavaScript; write clear, testable code.
• Working knowledge of SQL and relational databases.
• Understanding of data structures, algorithms, and software fundamentals.
• Strong analytical and problem-solving skills.
• Clear written and verbal communication; able to collaborate in a team.
• Curiosity, accountability and willingness to learn new technologies.

Responsibilities

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

Skills

Python

SQL

HTML

JavaScript

Data structures

Algorithms

Analytical thinking

Communication

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Electronics Engineering or related technical discipline

Tools

Databricks

Azure

Git

CI/CD

Job description

Data Engineering Summer/Fall Co-Op (June - Dec '27)

Posting Start Date: 8/28/26. Job Location(s): Irvine.

Requisition ID:78285

Description

Data Engineering Intern

We are looking for a motivated Data Engineering Intern 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 internship is for June/July to December 2027 time period.

Responsibilities

What You Will Work On

• Develop and maintain data ingestion and transformation pipelines using Python, SQL, PySpark, HTML, JavaScript, 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.

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 Will Learn

• Databricks & Spark - Develop notebooks and scalable transformations with SQL, Python, PySpark, HTML, and JavaScript.
• 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.

Ideal Candidate Profile

• Takes ownership of assigned work and communicates progress or blockers early.
• Approaches problems methodically and validates results before considering work complete.
• Can learn independently while seeking guidance at the right time.
• Values clean code, documentation, data security, and reliable delivery.
• Is interested in building a long-term career in data engineering and cloud data platforms.

Suggested Academic or Personal Projects

• An end-to-end ETL pipeline that ingests, cleans, transforms, and publishes a dataset.
• A Databricks or Spark project using Delta tables and Bronze, Silver, and Gold layers.
• A data quality or reconciliation framework using Python and SQL.
• A cloud-based analytics project with Azure storage, orchestration, and reporting.
• A database design, API ingestion, or data visualization project with clear documentation.

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.
• Must have the ability to work on-site 5 days per week.
• Basic programming proficiency in Python, with familiarity in HTML and JavaScript, 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.

Desired Experience and Skills

• 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 SQL.
• Understanding of ETL/ELT, data warehousing, lakehouse, or medallion architecture concepts.
• Familiarity with HTML, JavaScript, Git, Azure DevOps, CI/CD, Linux, REST APIs, or Power BI.
• Awareness of data governance, security, access control, or data quality principles.
• Databricks or Microsoft Azure learning credentials are an advantage but not required.

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 [e-mail].