Senior Data Engineer — Data Platform & Analytics

Kent State University; Kent (OH); On-site; USD 77,000 - 85,000; Full time

Job summary

Kent State University is seeking a Senior Data Engineer on the Kent Campus in Kent, OH to help modernize the university's analytics and integration platforms. You will design and build scalable data pipelines, data models, and enterprise integrations, connecting information from systems across the institution.

The role spans analytics and data engineering initiatives, enables university-wide analytics, reporting, and data services, and requires strong SQL, data modeling, and data governance

Qualifications

• Bachelor’s degree in computer science, information technology or a related field.
• Minimum of five years progressive experience in data engineering, data warehousing, and analytics.
• Experience with relational databases and data modeling.
• Experience with ETL/ELT design and data integration.
• Strong SQL skills and data quality metrics.

Responsibilities

• Create and maintain data lake, data mart, data warehouse and data integration architectures.
• Assemble large, complex data sets meeting functional/non-functional business requirements.
• Identify and implement data process improvements for scalability and data integrity.
• Build ETL/ELT pipelines from cloud, hybrid, and on-premises sources.
• Coach and perform code reviews for team members and data professionals across the university.
• Develop data lifecycle management in the modern data warehousing environment.

Skills

Relational DBs

Data modeling

Data integration

Advanced SQL

Data transformation

Data governance

Documentation

Education

Bachelor’s degree in CS/IT or related field

Job description

Kent State University is seeking a Senior Data Engineer on the Kent Campus in Kent, OH to help modernize the university's analytics and integration platforms. You will design and build scalable data pipelines, data models, and enterprise integrations, connecting information from systems across the institution.

The role spans analytics and data engineering initiatives, enables university-wide analytics, reporting, and data services, and requires strong SQL, data modeling, and data governance