Hybrid Data Engineer Intern: Cloud Migrations & BI
BYU Pathway
Riverton (UT)
Hybrid
USD 20,664 - 34,440
Full time
14 days+
Get more replies from employers
Send a job-specific resume in minutes.
Start fresh or import an existing resume
Benefits offered by this job
High deductible medical plan option
Mentorship from experienced professionals
Job summary
A leading educational organization seeks a Data Engineer Intern for a hybrid position in Riverton, UT. This role involves working with experienced mentors to develop information solutions, facilitating better decisions for Church departments. Applicants should be enrolled in or recent graduates from accredited institutions and demonstrate strong analytical skills. The internship spans four months, with a focus on using technology to support welfare efforts and enhance efficiencies in data management.
Qualifications
Currently enrolled or within one year of graduation from an accredited college or university.
Solid aptitude for learning business intelligence tools.
Effective communication skills for management interaction.
Responsibilities
Support systems and deliver services to users at Church headquarters.
Work with teams to build process models and compile reports.
Monitor processes and make recommendations for efficiency.
Skills
Business intelligence tools aptitude (Tableau, Power BI)
Data understanding
Communication skills
Analyzing large data
Business presentation skills
Organizational skills
Attention to detail
Technology background
Education
Currently enrolled college/university or within one year of graduation
Job description
A leading educational organization seeks a Data Engineer Intern for a hybrid position in Riverton, UT. This role involves working with experienced mentors to develop information solutions, facilitating better decisions for Church departments. Applicants should be enrolled in or recent graduates from accredited institutions and demonstrate strong analytical skills. The internship spans four months, with a focus on using technology to support welfare efforts and enhance efficiencies in data management.