Data Engineering Internship at The Middleby Corporation

Elgin, Illinois, United States -

Full Time

Start Date

Immediate

Expiry Date

29 Jun, 26

Salary

0.0

Posted On

31 Mar, 26

Experience

0 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Azure Data Factory, Azure Synapse, Microsoft Fabric, SQL, Python, Azure Data Lake, Data Pipeline Development, Data Exploration, Data Profiling, Data Cleaning, Data Transformation, Data Validation, ETL/ELT, Data Modeling, Machine Learning, AI Tools

Industry

Machinery Manufacturing

Description

Description Middleby is a fast-growing, pro?table global manufacturer of commercial foodservice equipment headquartered in Elgin, Illinois. The company markets its products under a broad portfolio of industry-leading brands and operates manufacturing and distribution facilities around the world. Since 2001, Middleby has experienced significant growth and was named one of Fortune Magazine’s Fastest Growing Companies. In 2022, Middleby was recognized by Forbes as one of the World’s Best Employers and is a proud philanthropic partner to organizations addressing food insecurity. Are you passionate about data, cloud platforms, and solving real-world analytics challenges? Middleby is seeking a motivated Data Engineering Intern to join our Digital Technology team for Summer 2026. This internship offers hands-on exposure to enterprise-scale data systems, Azure-based cloud technologies, and cross-functional collaboration on meaningful business initiatives. As an intern, you will assist in building, testing, and optimizing modern data pipelines while gaining experience with tools and technologies such as Azure Data Factory, Azure Synapse, Microsoft Fabric, SQL, and Python. You will also support the design and implementation of data analytics frameworks, performing data cleaning, transformation, and validation to ensure high standards of data quality, accuracy, and integrity. Throughout the program, you’ll receive mentorship from experienced professionals and have the opportunity to contribute to impactful projects within a global organization. Responsibilities: Support Data Pipeline Development: Assist in building and modifying ETL/ELT pipelines using tools like Azure Data Factory and Synapse Analytics. Data Exploration & Profiling: Conduct initial data analysis using SQL and Python, helping assess data quality, completeness, and structure. Cloud Data Work?ows: Work with cloud-based storage (e.g., Azure Data Lake) and contribute to optimizing performance for ingestion pipelines. Documentation: Create technical documentation for processes, scripts, and con?gurations you contribute to. Collaborative Projects: Participate in team scrums, engage with stakeholders, and gain insights into the broader business applications of data. Experiment with Innovation: Test out new Azure services in sandbox environments like Microsoft Fabric and share ?ndings with the team. Requirements: Currently Enrolled in a Bachelor's or Master’s program in Computer Science, Data Science, Information Systems, or a related technical ?eld. Academic Exposure to cloud platforms, preferably Microsoft Azure, and basic understanding of data engineering concepts. Comfortable with Code: You have experience writing scripts in SQL and/or Python (either through coursework or personal projects). Detail-Oriented: You love digging into data and noticing inconsistencies others might miss. Fast Learner & Communicator: You’re eager to pick up new tools and can explain your ideas clearly. Exposure to Azure services like Data Factory, Data Lake, or Synapse (through school, projects, or certi?cations). Familiarity with data modeling or building small-scale pipelines. Interest in machine learning, AI tools, or data visualization platforms like Power BI. Middleby Corporation is an Equal Employment Opportunity (EOE/M/F/Vets/Disabled) employer and welcomes all qualified applicants.

Responsibilities

The intern will assist in building, testing, and optimizing modern data pipelines using tools like Azure Data Factory and Synapse Analytics, while also supporting the design and implementation of data analytics frameworks. Responsibilities include performing data cleaning, transformation, and validation to ensure high data quality and integrity across cloud-based work flows.