People Data Intern
| Company | Qualtrics |
|---|---|
| Location | Provo, UT, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Internship |
| Degrees | Bachelor’s, Master’s |
| Experience Level | Internship |
Requirements
- Basic proficiency in SQL and Python, with knowledge of data integration techniques and tools.
- Understanding of data quality principles and data modeling concepts.
- Familiarity with ETL tools and processes.
- Basic knowledge of HR-related data structures.
- Strong attention to detail and ability to document processes clearly.
- Basic analytical and problem-solving skills.
Responsibilities
- Support People Data Collection and Integration: Help manage data collection processes from various sources, including exploring and potentially integrating data from external People system APIs. You may assist in scripting using Python and SQL and automation efforts using an orchestration tool, Prefect, for data ingestion.
- Assist with People Data Modeling and Documentation: Collaborate on building and refining data models and create clear and concise data diagrams to document data structures and relationships. You may also contribute to technical documentation of data processes.
- Data Collection and Integration: Contribute to the accurate and optimized creation and maintenance of materialized views and data sources in our Redshift data warehouse, under the guidance of the senior architect.
- Documentation: Produce and maintain clear documentation of data integration processes, workflows, and mapping for transparency and knowledge transfer.
- Problem Resolution: Identify emerging data quality issues and collaboratively work with the senior architect to resolve them. Assist in troubleshooting and resolving basic data integration challenges.
Preferred Qualifications
- Currently pursuing a Bachelor’s or Master’s degree in a relevant field such as Computer Science, Data Science, Data Analytics, Information Systems, Statistics, Mathematics, Economics, or a related technical discipline.
- Demonstrated coursework or personal projects involving SQL, data transformation (e.g. using Python with Pandas), and database concepts (e.g. entity relationship diagrams). Familiarity with APIs or data modeling principles is a plus.
- Evidence of strong analytical and problem-solving abilities, with a demonstrated curiosity to learn and understand complex data challenges.