Data Engineering Winter/Spring Co-Op (Jan-June ’27)

Job Description

Skyworks is an innovator of high-performance analog semiconductors whose solutions are powering the wireless networking revolution. 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. 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.
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
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, 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.
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.
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.
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.
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. 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. if you need an accommodation due to a disability, please contact us at accommodations@skyworksinc.