Institutional Data Engineer

University of South Carolina; South Carolina; On-site; USD 78,000 - 118,000; Full time

Benefits offered by this job

Health and life insurance

Generous retirement programs

Paid tuition

Annual leave

Sick leave

13 paid holidays

Job summary

University of South Carolina is seeking an Institutional Data Engineer to design, develop, and maintain enterprise data infrastructure and integration processes supporting analytics across the university ecosystem.

The role focuses on ETL/ELT pipelines, data quality, governance, and system modernization while ensuring reliability and availability of reporting platforms for Columbia campus and USC system institutions.

Qualifications

• Bachelor’s degree in a job-related field and 3 or more years of job-related experience; equivalent certifications or training may substitute.
• Strong problem-solving and communication skills; ability to work well across distributed teams.
• Proficiency in SQL, relational databases, ETL/ELT technologies, and data warehousing.
• Strategic vision and operational excellence to support IT service delivery.
• Comfort working collaboratively in a culture that values curiosity and innovation.

Responsibilities

• Provide scalable and reliable access to institutional data.
• Improve data accuracy, completeness, and consistency.
• Modernize the institution’s analytics capabilities.
• Lead enterprise-wide data engineering and integration projects as directed.
• Design, develop, and maintain enterprise data pipelines, ETL/ELT processes, system integrations, and automated workflows for institutional reporting and analytics.
• Collaborate with data architects to set technical standards and architect data models, data warehouses, and curated datasets.
• Create and optimize database objects, including views and stored procedures, to improve performance.
• Monitor and enhance data architecture for reliable data access.
• Support data integration across the Columbia campus and USC system institutions.
• Implement data validation, reconciliation, and quality assurance processes.

Skills

SQL

Data warehousing

ETL/ELT

Relational databases

Communication

Team collaboration

Education

Bachelor’s degree in data-related field

Tools

IBM DataStorage

Informatica

SSIS

Cognos

Tableau

PowerBI

Job description

The Institutional Data Engineer at the University of South Carolina designs, develops, maintains, and optimizes enterprise data infrastructure and integration processes to support dependable institutional analytics and reporting across the university ecosystem.

Role Overview

This position focuses on building and improving enterprise data pipelines (ETL/ELT), data integration workflows, and analytical data environments. The work includes data quality and governance support, system maintenance and modernization efforts, and ongoing monitoring to ensure reliability and availability of institutional reporting and analytics systems.

Key Responsibilities

• Provide scalable and reliable access to institutional data.
• Improve data accuracy, completeness, and consistency.
• Modernize the institution’s analytics capabilities.
• Lead enterprise-wide data engineering and integration projects and initiatives as directed.
• Design, develop, and maintain enterprise data pipelines, ETL/ELT processes, system integrations, and automated workflows for institutional reporting and analytics.
• Partner with data architects to set technical standards and architect or optimize enterprise data models, data warehouses, curated datasets, and database objects to enable scalable, secure, and reliable access.
• Create and optimize database objects, including views and stored procedures, to improve performance and scalability.
• Monitor and enhance data architecture to ensure efficient, reliable access to institutional data.
• Support data integration across the Columbia campus and university system institutions to improve consistency and comparability of reporting.
• Implement data validation, reconciliation, and quality assurance processes, and resolve data discrepancies across source systems and analytical datasets.
• Develop automated monitoring and exception reporting to proactively detect data quality issues.
• Collaborate with data stewards and functional offices to recommend, establish, and maintain data standards and business rules.
• Support enterprise data governance and data stewardship practices.
• Maintain system documentation, process documentation, technical specifications, and metadata.
• Maintain and support enterprise data platforms, reporting databases, and data integration environments.
• Monitor system performance, troubleshoot issues, and implement corrective actions to ensure reliability and availability.
• Perform routine maintenance, upgrades, testing, and deployment activities for data infrastructure and integration processes.
• Respond to technical support requests related to institutional reporting and analytics systems.
• Assist with change management, backup procedures, disaster recovery, and business continuity planning for institutional data systems.
• Research, evaluate, and recommend emerging technologies, tools, and methodologies to enhance institutional analytics and data management capabilities.
• Identify opportunities to automate manual processes and improve operational efficiency.
• Participate in the development of reporting, dashboarding, and self-service analytics solutions.
• Support modernization initiatives involving cloud technologies, advanced analytics, and data platform enhancements.
• Contribute to continuous improvement efforts that increase the effectiveness of institutional data services.
• Partner with institutional research, information technology, academic units, administrative offices, and campus stakeholders to understand business needs and reporting requirements.
• Provide technical consultation and guidance regarding data availability, structure, and reporting capabilities.
• Support training and knowledge-sharing activities, including mentoring junior engineers and technicians across the USC system.
• Perform other duties assigned by the AVP for IT Enterprise AI, Data, and Research Computing, the Director of Institutional Data Analytics, or your supervisor to support strategic and operational needs.
• Participate in professional development activities and maintain awareness of emerging trends, regulations, and recommended practices.
• Support university committees, working groups, special projects, system-wide initiatives, and executive requests as needed.

Required Qualifications

• Bachelor’s degree in a job-related field and 3 or more years of job-related experience; an equivalent combination of job-related certification, training, education, and/or experience may substitute for the requirement.
• Strong problem-solving and communication skills; ability to work well across distributed teams.
• Demonstrated proficiency in data engineering technologies and processes, including SQL, relational databases, and ETL/ELT technologies, plus data warehousing.
• Strategic vision and operational excellence to support IT service delivery.
• Comfort working collaboratively in a culture that values curiosity and innovation.

Preferred Qualifications

• Bachelor’s degree in Data Analytics, Information Systems, Computer Science, Statistics, or a related field.
• Strong proficiency in ETL tools (IBM DataStorage, Informatica, SSIS) and BI tools (Cognos, Tableau, PowerBI), including recommended configuration and security practices in hardware and cloud-based server environments.
• Strong proficiency in SQL for data querying, transformation, and optimization.
• Experience with relational databases including Oracle, SQL Server, or PostgreSQL.
• Familiarity with data warehouse concepts and dimensional modeling.
• Strong analytical and problem-solving skills with attention to detail.
• Excellent communication skills and ability to collaborate in a team environment.
• Experience working in higher education or the public sector.
• Experience with enterprise data systems (HR, Finance, Student Information, Learning Management) and large-scale institutional datasets.

Technical Skills and Tools

SQL, relational databases, ETL/ELT technologies, data warehousing, IBM DataStorage, Informatica, SSIS, Cognos, Tableau, PowerBI, Oracle, SQL Server, PostgreSQL, dimensional modeling, cloud technologies, database objects, data models, data warehouses, stored procedures, views, automation, dashboards, self-service analytics, and data integration environments.

Compensation and Location

• Location: Richland, SC (onsite)
• Salary: USD 78,441 - 117,662 per yearly
• Minimum Experience: 3 years

Benefits

• Health and life insurance
• Generous paid leave and retirement programs
• Research Grant or time-limited positions may be eligible for all, some, or no benefits based on grant or project funding
• Paid tuition
• Dependent scholarships
• Annual leave
• Sick leave
• 13 paid holidays (including an extended December holiday)
• Paid parental leave
• Professional development opportunities

Safety-Sensitive Position Information

• Employees in Safety-Sensitive or Security-Sensitive positions are subject to pre-employment and post-employment drug testing in accordance with University policy HR 1.95 Drug and Alcohol Testing.
• Safety Sensitive or Security Sensitive: No
• Hazardous weather category: Non-Essential