Data ETL Engineer

Job Posting Title:

Data ETL Engineer

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Hiring Department:

Data to Insights

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Position Open To:

All Applicants

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Weekly Scheduled Hours:

40

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FLSA Status:

Exempt

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Earliest Start Date:

Immediately

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Position Duration:

Expected to Continue Until Aug 31, 2026

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Location:

Texas

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Job Details:

General Notes

The Data to Insights (D2I) Initiative at UT Austin is an investment to build a trusted, integrated, and scalable information infrastructure that transforms complex UT data into valued insights for data-informed decisions.

As a team member in the Data to Insights (D2I) Initiative, you will work with a cross-campus team using the latest cloud technologies to build a next-generation data warehouse that will improve decision-making and advance the university’s mission. We believe the best ideas arise from collaborative work among colleagues from varied backgrounds and experiences. If you’re the type of person who loves to learn and wants to know your work has meaning, you may find your career home at UT Austin. Please note that this position is currently funded through August 31, 2026.

The University of Texas at Austin provides an outstanding benefits package to staff, including: 

• Competitive health benefits (Employee premiums covered at 100%; family premiums at 50%) 
• Vision, dental, life, and disability insurance options 
• Paid vacation, sick leave, and holidays 
• Teachers Retirement System of Texas (a defined benefit retirement plan) 
• Additional voluntary retirement programs: tax sheltered annuity 403(b) and a deferred compensation program 457(b) 
• Flexible spending account options for medical and childcare expenses 
• Training and conference opportunities 
• Tuition assistance 
• Athletic ticket discounts 
• Access to UT Austin's libraries and museums 
• Free rides on all UT Shuttle and Capital Metro buses with staff ID card 

For more details, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards 

This position requires you to maintain internet service and a mobile phone with voice and data plans to be used when required for work.

This position provides life/work balance with typically a 40-hour work week and travel generally limited to training (e.g., conferences/courses).

Purpose

The Data ETL Engineer for the UT Data Hub improves university outcomes and advances the UT mission to transform lives for the benefit of society by increasing the usability and value of institutional data.

The Data ETL Engineer develops extract, transform, and load (ETL) procedures using integration tools such as Informatica for complex data models that reflect academic and administrative business processes at the University of Texas at Austin.  The Data ETL Engineer plays a critical part in establishing a valuable cloud data warehouse that supports critical business decisions and data analysis processes for the campus community. The Data ETL Engineer leverages their creativity to solve complex data and business problems and builds effective relationships through open communication.

Responsibilities

Development & Design:

• Develop ETL programs for complex dimensional data models within modern data platforms such as AWS Aurora Postgres, Snowflake, etc.
• Interpret and devise data mapping documents
• Design and automate ETL solutions for data cleansing, preparation, data validation and related processes

Adaptation & Maintenance:

• Adapt ETL programs to evolving data models and business needs
• Adapt ETL programs in response to data quality assurance findings

Communication & Collaboration:

• Partner with key stakeholders including enterprise data architect, subject matter experts (SMEs), data modelers, and teammates
• Guide complex technical projects, enabling effective communication and collaboration with project stakeholders

Other duties as assigned.

Required Qualifications

• BS degree in Computer Science, Information Systems, Engineering, or equivalent professional experience.
• Two years of experience designing and implementing ETL technical solutions for complex data models