This article outlines the Data Analyst Intern role, focusing on the position’s purpose, core responsibilities, and required skills. It organizes the provided role overview, details the day‑to‑day tasks such as data collection, cleaning, reporting and automation, and lists the technical and professional requirements. Use this as a clear reference for what the role expects and what capabilities are needed.
Role and purpose
The Data Analyst Intern is expected to transform raw data into meaningful insights that support business decisions. The role centers on preparing and analyzing large datasets, producing reports and dashboards, automating repetitive reporting, and collaborating with multiple teams to inform action.
Key responsibilities
- Collect, clean and preprocess large datasets using Excel, SQL, and Python (Pandas).
- Write optimized SQL queries to extract and manipulate data.
- Design and maintain interactive dashboards and reports with Power BI, Tableau, or Google Data Studio.
- Automate repetitive reporting tasks using Excel macros or Python scripts.
- Collaborate with cross-functional teams including marketing, operations, and finance.
- Generate weekly and monthly performance reports that include actionable recommendations.
Required skills and expectations
The role requires both technical tools and professional behaviors. Candidates must demonstrate practical proficiency and readiness to contribute independently.
- MS Excel proficiency, including VLOOKUP, PivotTables and advanced formulas; plus basic data cleaning techniques.
- Working knowledge of SQL for querying and data manipulation.
- Familiarity with Python libraries such as Pandas and NumPy, and plotting with Matplotlib or Seaborn.
- Basic understanding of statistics and data visualization principles.
- Ability to work independently and meet deadlines.
- Willingness to relocate at short notice if required.
In summary, the Data Analyst Intern role combines data preparation, analytical querying, dashboarding, automation and cross‑team collaboration. The position expects proficiency in Excel, SQL and Python tools, a grounding in statistics and visualization, the ability to deliver timely reports with recommendations, and the flexibility to relocate quickly if needed.
