Senior Data Engineer

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 ecosystem 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 : and

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 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 useability and value of institutional data.

You will create complex data pipelines into UT’s cloud data ecosystem in support of academic and administrative needs. In collaboration with our team of data professionals, you will help build and run a modern data hub to enable advanced data-driven decision making for UT.

You will leverage your creativity to solve complex technical problems and build effective relationships through open communication.

Responsibilities

Data Engineering :

• Providing leadership, guidance, and execution as it relates to designing and automating scalable data integration solutions between institutional data sources, including the UT source systems, Amazon Web Services, and vendor APIs
• Assure performance and reliability of integration processes through monitoring, performance analysis and development of automated alerting processes.
• Participate in end-to-end delivery of technical projects involving design and development of advanced data pipelines for complex datasets.
• Work closely with business partners to design and manage data pipeline elements including load frequency, data delivery mechanisms, and transformations.
• Ensure that data pipeline solutions align with industry best practices, and adhere to UT security guidelines.
• Develop and maintain detailed technical documentation of data pipeline processes.
• Collaborate with key stakeholders including enterprise data architect, data modelers, data stewards, and subject matter experts (SMEs).
• Actively participate in improving data engineering processes and pipelines.
• Proactively learn about the latest technologies and emerging trends in the data engineering space that may be applicable to our work in D2I.

Collaboration, Support, & Communication :

• Work independently and collaboratively with cross-functional teams to develop exceptional technical products that meet University needs.
• Effectively communicate project status, progress, risks and issues to drive projects to completion.
• Organize and promote productive, creative, and collaborative interactions within the Data Engineering team to brainstorm, develop, implement, and refine scalable processes for the team.
• Foster a supportive environment for team morale and team engagement.
• Provide peer coaching and guidance to junior data engineers in all aspects of their work.
• Participate in change management processes to coordinate and communicate team activity.

Required Qualifications

• BS degree in Computer Science, Information Systems, Engineering, or equivalent professional experience.
• At least three years of Data Engineering experience with Amazon Web Services.
• Three years of experience implementing and monitoring complex data pipelines and automation of cloud-based workloads.
• Proficiency in one or more scripting languages and / or programming languages, preferably Python.
• Advanced SQL knowledge and experience working with relational databases.
• Demonstrated experience of developing and implementing Continuous Integration and Continuous Delivery (CI / CD) systems.
• Proficiency in systems analysis, design, and a solid grasp of development, quality assurance, and integration methodologies.
• Excellent problem solving and troubleshooting skills.
• Strong communication skills and customer service.
• Experience with mentoring junior engineers.

Preferred Qualifications

• Five or more years of experience in Data Engineering or related field.
• Three or more years mentoring or supervising others.
• Two years of experience working in a cloud-based data warehouse environment.
• Three or more years of experience building and monitoring complex data pipelines.
• AWS Developer and / or Solutions Architect certification.
• At least two years of experience with Agile software development methodologies.
• At least two years of experience with issue tracking systems (JIRA).
• Experience with Spark, Kafka etc., is a plus.

Salary Range

$115,000 + depending on qualifications

Working Conditions

• May work around standard office conditions
• Repetitive use of a keyboard at a workstation
• Use of manual dexterity
• Up to 100% remote at employee discretion with office work environment also an option. Majority of team is located in Austin, TX, and working remotely with infrequent in-office presence.

Required Materials

Resume / CV

• 3 work references with their contact information; at least one reference should be from a supervisor
• Letter of interest

Important for applicants who are NOT current university employees or contingent workers : You will be prompted to submit your resume the first time you apply, then you will be provided an option to upload a new Resume for subsequent applications.

Any additional Required Materials (letter of interest, references, etc.) will be uploaded in the Application Questions section;

you will be able to multi-select additional files. Before submitting your online job application, ensure that ALL Required Materials have been uploaded.

Once your job application has been submitted, you cannot make changes.

Important for Current university employees and contingent workers : As a current university employee or contingent worker, you MUST apply within Workday by searching for Find UT Jobs.

If you are a current University employee, log-in to Workday, navigate to your Worker Profile, click the Career link in the left hand navigation menu and then update the sections in your Professional Profile before you apply.

This information will be pulled in to your application. The application is one page and you will be prompted to upload your resume.

In addition, you must respond to the application questions presented to upload any additional Required Materials (letter of interest, references, etc.

that were noted above.

Employment Eligibility :

Regular staff who have been employed in their current position for the last six continuous months are eligible for openings being recruited for through University-Wide or Open Recruiting, to include both promotional opportunities and lateral transfers.

Staff who are promotion / transfer eligible may apply for positions without supervisor approval.

Retirement Plan Eligibility :

The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length.

Background Checks :

A criminal history background check will be required for finalist(s) under consideration for this position.