Intern, IT Data Analytics (2027)

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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 ve