Data Engineer, Center for Media Engagement, Moody College of Communication

UT MAIN CAMPUS, United States

The University of Texas at Austin

USD 85K+ Full Time Mid

Company preview All jobs at The University of Texas at Austin

Apply Job profile

Published 4 days ago

Job Posting Title:

Data Engineer, Center for Media Engagement, Moody College of Communication

----

Hiring Department:

Media Engagement, Center for

----

Position Open To:

All Applicants

----

Weekly Scheduled Hours:

----

FLSA Status:

Exempt

----

Earliest Start Date:

Immediately

----

Position Duration:

Expected to Continue Until May 31, 2026

----

Location:

UT MAIN CAMPUS

----

Job Details:

General Notes

This position will end May 31, 2026 with the possibility of continuation depending on availability of grant funding and work performance.

Purpose

This role is eligible for hybrid or fully remote work. The Data Engineer will support the Center for Media Engagement's research on connective democracy.

Responsibilities

Maintain a data archive system with archives of static and streaming internet and news data that can be queried by researchers.
Seek out, collect (via API, crawling, or another method) and support new datasets that are of interest to CME faculty.
Manage the security of the archive, including access, encryption, and security training. Regularly review security measures, permissions, and encryption protocol.
Manage data back-ups. Store and update documentation of datasets, including provenance files/data sheets, access protocols, and security measures. This may involve some software development.
Document the process and contribute to research and open-source initiatives, including writing datasheets for datasets.
Wrangle data and perform extract-transform-load procedures.
Work with and support researchers with various backgrounds in computational methods to inform their research designs.
Other duties as assigned.

Required Qualifications

Bachelor's degree with relevant experience.
Technical Skillset: Python (pandas, numpy), R, SQL/Hadoop, Tensorflow/Keras/Huggingface, Github, unix/cmd, github,
Familiarity with AWS/Azure/GCP cloud infrastructure.
Experience using Rest APIs and/or data scraping
Experience working with multiple project and collaborating with teams
Clear and timely communication

Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

Masters degree in computer science or information
Six years of relevant experience.
Knowledge in machine learning
Ability to develop and optimize data science software
Experience working with social media data
Knowledge of or experience with signal processing, computer vision, or network analysis
Experience with open-source software/OSINT
Develop, implement, and evaluate supervised and unsupervised classifiers, including training and testing classifiers (e.g., BERT, GPT, CNN) for multiple research projects.
Recommend and execute strategies to improve model performance and efficiency.
Follow emerging trends in computational research (e.g. RAG, RLHF) and use these learnings to inform researchers of how they could apply to their work.

Salary Range

$85,000 + depending on qualifications

Working Conditions

Typical office environment

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.

----

Equal Opportunity Employer:

The University of Texas at Austin, as an equal opportunity/affirmative action employer, complies with all applicable federal and state laws regarding nondiscrimination and affirmative action. The University is committed to a policy of equal opportunity for all persons and does not discriminate on the basis of race, color, national origin, age, marital status, sex, sexual orientation, gender identity, gender expression, disability, religion, or veteran status in employment, educational programs and activities, and admissions.

----

Pay Transparency:

The University of Texas at Austin will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the contractor’s legal duty to furnish information.

----

Employment Eligibility Verification:

If hired, you will be required to complete the federal Employment Eligibility Verification I-9 form. You will be required to present acceptable and original documents to prove your identity and authorization to work in the United States. Documents need to be presented no later than the third day of employment. Failure to do so will result in loss of employment at the university.

----

E-Verify:

The University of Texas at Austin use E-Verify to check the work authorization of all new hires effective May 2015. The university’s company ID number for purposes of E-Verify is 854197. For more information about E-Verify, please see the following:

----

Compliance:

Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.

The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.

Apply