Senior Data Engineer, ETL & Analytics (Hybrid)

University of Tennessee Foundation, Inc; Knoxville (TN); Hybrid; USD 100,000 - 150,000; Full time

Benefits offered by this job

Hybrid schedule

Education benefits for employees and/或

UT System campuses education benefits

401(k) and 403(b) retirement plans

Medical, dental, and vision insurance

Employee discounts

Job summary

The University of Tennessee Foundation, Inc. is seeking a Data Engineer to build and support enterprise ETL pipelines across cloud and on-prem environments in a hybrid Knoxville, TN setting.

You will implement, monitor, and optimize data pipelines connecting Salesforce, Tableau, SFTP, and enterprise data warehouses; collaborate with BI analysts and Data Platform teams to deliver trusted reporting and analytics; and ensure governance, security, and documentation are maintained.

Qualifications

• Bachelor’s degree required.
• 5+ years of experience in business intelligence, enterprise data engineering, analytics, or related disciplines.
• Experience designing enterprise data architecture.
• Experience developing ETL/ELT initiatives.
• Experience supporting enterprise CRM platforms, preferably Salesforce.
• Experience developing enterprise reporting and analytics solutions.
• Experience managing cloud-based data environments, preferably Fabric and/or Azure.
• A valid driver’s license with travel responsibilities.

Responsibilities

• Implement, monitor, maintain, and troubleshoot enterprise ETL and data pipelines connecting Salesforce, cloud platforms, SFTP environments, Tableau, and enterprise data warehouse solutions.
• Rerun failed ETL jobs, reporting tables, and scheduled integration processes to keep reporting and operational data available on time.
• Support daily data processing and time-sensitive reporting needs.
• Monitor pipeline execution and tune existing integrations to identify issues early and improve reliability for downstream analytics.
• Develop and maintain reporting views, transformation logic, curated datasets, and semantic-layer objects used for BI and analytics initiatives.
• Translate business and reporting requirements into reporting-ready datasets and reusable transformation processes.
• Create and update data warehouse objects including tables, views, and stored procedures, including onboarding new Salesforce fields and data sources into enterprise reporting environments.
• Standardize business logic, KPI calculations, and reporting definitions; optimize query and semantic-layer performance across analytics platforms.
• Collaborate with BI analysts, CRM administrators, and Data Platform teams to support reporting, dashboarding, and operational data requirements.
• Prepare and curate datasets that support Data Science, predictive modeling, and AI initiatives.
• Participate in discussions related to business requirements, reporting structures, and analytics solutions.
• Communicate technical issues, integration impacts, and implementation updates clearly to technical and non-technical stakeholders; provide troubleshooting support for reporting and data integration issues.
• Maintain technical documentation for ETL pipelines, workflows, transformation logic, semantic-layer objects, configurations, and support procedures.
• Follow established standards and best practices for data governance, security, and change management.
• Research emerging cloud, ETL, semantic modeling, and data engineering technologies to improve operational efficiency and reporting capabilities.
• Participate in training and professional development in data engineering, cloud data platforms, and analytics engineering practices.

Skills

Enterprise data architecture

ETL/ELT initiatives

CRM platforms experience

Education

Bachelor’s degree

Tools

Salesforce

Microsoft Fabric

Azure Data Factory

Tableau

SFTP

Job description

The University of Tennessee Foundation, Inc. is seeking a Data Engineer to build and support enterprise ETL pipelines across cloud and on-prem environments in a hybrid Knoxville, TN setting.

You will implement, monitor, and optimize data pipelines connecting Salesforce, Tableau, SFTP, and enterprise data warehouses; collaborate with BI analysts and Data Platform teams to deliver trusted reporting and analytics; and ensure governance, security, and documentation are maintained.