Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Data Engineering Winter/Spring Co-Op (Jan-June '27)
Irvine, CA, US, 92617
Live, first seen by us 75 days ago- Pay
Multiple pay amounts — pay source
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 $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $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@skyworks.com.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- New graduates
- For current students
Job title: Data Engineering Winter/Spring Co-Op (Jan-June '27) (Irvine, CA, US, 92617)
What you’ll work on
Full postingBuild and maintain ETL/ELT pipelines in Python, SQL, PySpark, and Databricks notebooks
Orchestrate, schedule, and troubleshoot jobs with Databricks Workflows
Apply data profiling, validation, and quality checks to improve reliability
Help onboard new datasets into Azure Data Lake Storage and Databricks
Support pipeline monitoring, root-cause analysis, and defect resolution
From the employer’s posting
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.
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.
Education & alternatives
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 onsite 5 days per week
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 28, 202675 days ago
- Recorded sightings
- 268
- Last seen by us
- Nov 12, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 75
Up longer than most. Similar jobs usually come down between day 6 and day 55.
Well past Skyworks’s usual: its jobs come down by about day 12.
From 13,175 similar postings that came down, and 13 of Skyworks’s. Coming down is not always a hire.
Skyworks is hiring
12 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- JavaScript
- Python
- SQL
- Azure
- Databricks
- Delta Lake
- Power BI
- Spark
- PySpark
Where the posting names them
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.
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.
- Must have the ability to work onsite 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 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.
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
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.
- 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.
- 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.
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 January to June 2027 time period.
- 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 $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $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.
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.
Your next step
Complete your application on careers.skyworksinc.com. The employer’s form will show what is required.
Applying through SAP SuccessFactors
- Images (.jpg) aren’t accepted as a resume.
Already applied? Track this application
Has Skyworks posted this job before?
Yes. We’ve followed one other Data Engineering Winter/Spring Co-Op (Jan-June '27) job there since August 2026. It is still up.
About Skyworks
- People
- About 10,000 in 2025, down 1% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as SWKS.
- H-1B visas
- 56 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
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: 78284
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 January to June 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 onsite 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 $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $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@skyworks.com.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
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 $29.00 - $49.00 per hour and for a Non-Engineering intern across the U.S. is currently USD $23.00 - $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@skyworks.com.
- Location & working pattern
Irvine, CA, US, 92617
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.