Data Analysis Intern

We are seeking a motivated and detail-oriented Data Analyst Intern who is eager to learn and contribute to real-world data projects. As an intern, you will support the data team in transforming raw data into meaningful insights, building foundational data pipelines, and delivering accurate reports that enable data-driven decision-making across the organization. Key Responsibilities Assist in building and maintaining data pipelines using Python, Pandas, and Polars, under guidance from senior team members. Support data cleaning, transformation, and validation, ensuring high data quality and consistency. Help develop and maintain data models used for reporting and analytics. Work with analysts and business stakeholders to understand data requirements and translate them into datasets or reports. Contribute to automated reporting and dashboard workflows, where applicable. Perform exploratory data analysis to identify trends, anomalies, and actionable insights. Clearly document data logic, assumptions, and processes for reusability and transparency. Take ownership of assigned tasks, proactively flag issues, and suggest improvements rather than waiting for instructions. Demonstrate a problem-solver’s mindset—digging deeper into data issues and following through until resolution.

Must-Have Skills Good knowledge of Python. Working knowledge of SQL (joins, aggregations, CTEs, window functions). Familiarity with Pandas for data manipulation. Strong analytical and problem-solving skills. A go-getter attitude with the ability to take initiative and deliver outcomes, not just complete tasks. Willingness to learn new tools and technologies quickly. Ability to work independently while taking feedback constructively. Good communication skills and strong attention to detail.

Nice to Have Exposure to PySpark or Polars. Basic understanding of ETL/ELT concepts and data workflows. Familiarity with Git or version control systems. Awareness of cloud platforms such as Azure or tools like Databricks. Fundamental understanding of data structures and algorithms.