Description:
As a Commercial Data Intern, you will support the Commercial Data team by building and enhancing Power BI dashboards that improve data transparency, data quality monitoring, and decision‑making across key commercial workflows. You will gain hands‑on experience working with real commercial datasets such as Contacts, Users, Opportunities, and Quotes, while also contributing to data governance through structured documentation. This role offers practical exposure to data extraction, transformation, validation, visualization, and enterprise‑level reporting standards.
Key Responsibilities
- Assist in the development, enhancement, and maintenance of Power BI dashboards for Commercial datasets including Contacts, Users, Opportunities, and Quotes.
- Extract, transform, and validate data from source systems to ensure accuracy, completeness, and consistency in reporting.
- Collaborate with Commercial Data, Rev Ops, and other stakeholders to understand reporting needs and translate them into effective dashboard designs.
- Identify data quality gaps and support efforts to improve visibility into Commercial processes and workflows.
- Create and maintain a comprehensive field mapping dictionary, clearly documenting field definitions, purpose, usage guidelines, dependencies, and ownership.
- Develop clear process and logic documentation to support long‑term usability, onboarding, and alignment with global teams.
- Perform basic data validation and reconciliation to ensure dashboards reflect trusted and reliable data.
- Follow established data governance, documentation, and reporting best practices.
Required Qualifications
- Students graduating in the year 2027 specializing in Data Analytics, Business Analytics, Information Systems, Computer Science, Statistics, or a related field.
- Basic understanding of data concepts such as datasets, tables, fields, relationships, and data quality principles.
- Familiarity with Power BI, Excel, or other data visualization/reporting tools is preferred.
- Basic knowledge of data transformation concepts (e.g., filtering, joins, calculated fields).
- Strong analytical and problem‑solving skills with attention to detail.
- Ability to document processes and technical concepts clearly and concisely.
- Good communication and collaboration skills, with a willingness to learn in a fast‑paced, data‑driven environment.