Intern, IT Data Analytics (2027)

We Make Life More Rewarding and Dignified 

Location: ​WFH (US6)​
Department: ​ 

Summary

Embark on a hands-on journey in cloud data and analytics as our Summer 2026 Data & Analytics Intern. Based in Libertyville, Illinois, you will join Hollister’s Data Platforms & AI team to help build and optimize the next generation of our cloud data architecture. You will work with a modern cloud data and analytics stack including Microsoft Azure, Microsoft Fabric, SAP Business Data Cloud (BDC), SAP Datasphere, SAP Analytics Cloud (SAC), and Power BI to integrate, model, govern, and visualize enterprise data for actionable business insights.

From day one, you will contribute to key data initiatives: connecting data from core systems such as SAP into our Azure and Fabric analytics environment, developing robust data pipelines, and creating impactful visualizations. This role blends engineering and analytics, allowing you to build transformations while understanding the business purpose behind the data through collaboration with the teams using the dashboards and analytics solutions you help create.

Who should apply: Undergraduate and master’s students who are passionate about cloud data technologies and will return to school after the internship.

Hollister Incorporated operates in a hybrid environment, Interns are required to come into the office in Libertyville Illinois a minimum of 4 days per week. Hollister does not offer relocation nor housing assistance for this opportunity. 

Responsibilities

• Build & Manage Data Pipelines: Design, develop, and test data pipelines that integrate data from enterprise SAP and non-SAP sources into our Azure-based data platform. Use Azure Data Factory, Microsoft Fabric data integration capabilities, and related technologies to ingest and transform data reliably and efficiently. Support integration scenarios across SAP Business Data Cloud, SAP Datasphere, Microsoft Fabric, and Azure, including data flows into a Fabric Lakehouse for advanced analytics.
• Data Transformation & Modeling: Cleanse and transform raw data into analytics-ready datasets. Write SQL queries or Python scripts to combine, standardize, and aggregate data. Help define dimensional models and star schemas for cloud data warehouses and lakehouses, while learning to optimize transformations and queries in Azure Synapse and Microsoft Fabric.
• Dashboard & Report Development: Collaborate with analysts to develop and refine Power BI and SAP Analytics Cloud dashboards and reports. Connect analytics tools to trusted cloud datasets, create clear visualizations, support planning or executive reporting use cases, and improve solutions based on user feedback.
• Support Data Architecture Initiatives: Work with senior engineers on cloud data architecture projects, including OneLake storage, workspaces, and enterprise Fabric components. Support initiatives involving SAP Business Data Cloud and SAP Datasphere, including semantic modeling, data-sharing, and analytical patterns across SAP and Microsoft ecosystems. Explore approaches for integrating or modernizing legacy platforms such as SAP BW.
• Data Quality & Governance: Help implement data quality checks and governance practices by monitoring pipeline runs, validating outputs, and supporting data freshness and accuracy controls. Follow standards for naming, cataloging, lineage, security, and cloud resource tagging. Analyze usage or tagging metadata to support FinOps and cost transparency.
• Collaboration & Troubleshooting: Participate in stand-ups and project meetings. Work with data engineers, architects, analysts, business stakeholders, and global colleagues to diagnose failed pipelines, slow queries, reconciliation issues, or reporting defects. Propose practical fixes and gain experience with agile delivery methods.
• Research & Innovation: Research emerging capabilities in Azure, Microsoft Fabric, SAP Business Data Cloud, SAP Datasphere, and SAP Analytics Cloud. Explore improvements in data integration, governance,

Requirements:

• Education: Current enrollment in a Bachelor’s or Master’s program in Computer Science, Data Engineering, Information Systems, or a related field. Candidates should be returning to school after the internship (expected graduation after summer 2026 or later for undergrads, or 2026/2027 for master’s students).
• Foundational Skills: A solid understanding of databases and data concepts. Familiarity with SQL is required – you should be comfortable writing SELECT queries with JOINs, and you know what terms like “primary key” or “normalization” mean. Coursework or experience in data structures or algorithms is a plus as it underpins efficient data processing.
• Programming & Scripting: Experience with at least one programming or scripting language used in data handling, preferably Python (pandas, PySpark) or SQL-based scripting. Ability to write clear, logical code to transform data (for example, using Python to parse a CSV and load it into a database). Knowledge of version control (Git) and collaborative coding practices will be useful.
• Data Tools Knowledge: Exposure to data integration or analysis tools. This could be academic experience or self-taught projects using tools like Power BI, Tableau, or Excel for data visualization, and/or tools like ETL pipelines, databases, or cloud platforms for data processing. You don’t need to be an expert, but you should have curiosity and basic proficiency in working with data tools (for instance, having built a simple dashboard or a data pipeline in a class project).
• Analytical Mindset: Strong analytical and problem-solving skills. Ability to break down complex problems (e.g., figuring out why data doesn’t align across two systems) and a methodical approach to resolving them. Comfort with handling datasets, spotting anomalies or patterns, and using critical thinking to deduce causes and solutions.
• Communication & Teamwork: Good communication skills, both written and verbal. You should be able to document your work clearly and explain technical concepts in simple terms to team members or mentors. Collaboration is key – we’re looking for a team player who asks questions, listens to feedback, and is eager to learn from others. Since this internship is on-site, being proactive in face-to-face interactions and willing to engage with colleagues is essential.

Preferred Skills (Bonus)

• Cloud Platform Experience: Hands-on experience with cloud services, especially Microsoft Azure. Perhaps you’ve tried Azure in a class or personal project (e.g., deploying a web app, or using Azure Data Studio) or have familiarity with comparable services on AWS/GCP. Specific knowledge of Azure data services (such as Azure Synapse Analytics, Azure Data Factory, or Azure Databricks) would be a strong plus, as our environment heavily uses these technologies.
• Data Engineering Projects: Prior project or internship experience in data engineering or analytics. For example, having built a data pipeline, a simple data warehouse, or an interactive dashboard as a school project demonstrates useful practical skills. Experience with data transformation tools (ETL/ELT software, SQL scripts, etc.) or big data processing (Hadoop/Spark) could be beneficial.
• Knowledge of Microsoft Fabric & Power BI: Familiarity with Microsoft’s Fabric platform or Power BI. Maybe you’ve explored Fabric’s trial or are aware of its components (like Lakehouse, Data Factory, Power BI integration) from tech blogs or coursework. Experience creating Power BI reports or using Power BI Desktop to model data will help you contribute faster in our visualization tasks. Understanding how to publish reports to the Power BI Service or manage workspaces would be a bonus.
• SAP or ERP Data Understanding: While not required, any exposure to SAP systems or enterprise resource planning data is a plus. For instance, knowing what SAP is used for in business or having seen data from systems like SAP BW/HANA can help you quickly grasp our integration projects with SAP Datasphere. If you’ve taken courses related to enterprise systems or worked with large-scale ERP data, be sure to highlight that.
• Data Modeling & Analysis: Comfort with statistical analysis or data modeling concepts. This could include familiarity with dimensional modeling (facts/dimensions in a data warehouse) or experience analyzing data sets for insights. If you have used Python libraries (like NumPy, pandas) or analytics tools for a project (e.g., regression analysis, forecasting, etc.), it shows you can bring additional analytical thinking to the role.
• Attention to Detail: A knack for detail in working with data. For example, catching that data records don’t reconcile, or ensuring that a dashboard filter works correctly. In an environment dealing with multiple data sources and complex pipelines, being detail-oriented helps maintain data integrity (a critical trait when dealing with healthcare product data and global operations data that Hollister manages).
• Enthusiasm for Learning: A demonstrated eagerness to learn new technologies and concepts. The cloud data field evolves quickly – perhaps you’ve taught yourself a new programming language or completed an online course on your own. Show us that you’re proactive about learning (e.g., familiarity with communities or resources like Stack Overflow, Microsoft Learn, etc.) so we know you’ll embrace the chance to pick up whatever technologies our projects require.

The anticipated hourly rate for the position is $22.00 - $26.00 per hour based on applicant's education and skills. 

About Hollister Incorporated
Hollister Incorporated is an independent, employee-owned company that develops, manufactures and markets healthcare products worldwide. The company spearheads the advancement of innovative products for ostomy care, continence care and critical care, and also creates educational support materials for patients and healthcare professionals. Headquartered in Libertyville, Illinois, Hollister has manufacturing and distribution centers on three continents and sells in nearly 80 countries. Hollister is a wholly owned subsidiary of The Firm of John Dickinson Schneider, Inc., and is guided both by its Mission to make life more rewarding and dignified for people who use our products and services, as well as its Vision to grow and prosper as an independent, employee-owned company, and in the process, to become better human beings.

EOE Statement
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

Job Req ID: 36704