As a Data Analytics Intern, you will be expected to perform the following activities in alignment with your experience level:

• Write or collaborate on the creation of business requirements documents (BRDs) detailing solution characteristics, business expectations, and anticipated value.
• Create diagrams that illustrate high-level data domains and key concepts involved in solution design.
• Document required measures and KPIs to support business objectives, including clear definitions and calculation logic.

• Build and maintain detailed inventories of data assets required to deliver analytical solutions.
• Profile data assets to understand their granularity, domain context, business meaning, definitions, data quality characteristics, and interrelationships.

• Design scalable and reusable logical data models for analytical repositories using relational and dimensional modeling techniques, integrating and conforming data from multiple sources.
• Document entities, attributes, and relationships using logical data model diagrams.
• Define detailed data movement requirements to populate modeled entities, including column mappings, joins, load strategies, and load dependencies.
• Perform internal testing and system integration testing (SIT) on developed data assets.
• Collaborate with cross-functional teams to deliver end-to-end analytical solutions, including:
  • Data Governance teams for integration of master and reference data
  • Data Services / Engineering teams for ETL development
  • Business stakeholders for user acceptance testing (UAT)
  • Data Quality teams to support periodic data quality assessments
  • Report and dashboard developers, acting as a subject-matter expert (SME) on the designed data assets
  • Production Support teams for troubleshooting and issue resolution

• Design and implement semantic-layer data assets to support reports, dashboards, self-service analytics, and other downstream consumption scenarios.
• Create and maintain data dictionaries and documentation to enable and empower data consumers.

• Collaborate in backlog refinement, maintenance, and prioritization activities.
• Actively participate in agile ceremonies, contributing to discussions on current work, next steps, dependencies, and risks.
• Provide work breakdowns, effort estimates, and expected delivery timelines for assigned tasks.

• Work effectively with a high degree of independence in a remote or hybrid environment.
• Continuously expand professional value by learning emerging technologies and concepts and applying them to improve existing products, processes, and outcomes.

Required Qualifications – Experience, Skills, and Knowledge

• Completion of at least the 2nd year and current enrollment in the 3rd or 4th year of an undergraduate program in Mathematics, Computer Science, Statistics, Business Management, Information Systems, or a related field
• English proficiency at an advanced level (C1 or equivalent)
• SQL: basic data querying (DQL) skills
• Power BI: basic experience with report development or semantic model creation

Preferred Qualifications

• Familiarity with Data Warehouses, Data Lakes, or Data Lakehouse architectures
• Knowledge of relational and dimensional data modeling techniques
• Exposure to agile methodologies such as SCRUM and tools like Azure DevOps
• Awareness of cloud computing platforms such as Azure, Google Cloud, or Amazon Web Services, including Databricks
• Interest or foundational knowledge in AI concepts, including prompting techniques or agent development
• Exposure to Microsoft Fabric