Principal Data Engineer – Data Intelligence Manager

Job Posting Title:

Principal Data Engineer – Data Intelligence Manager

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Hiring Department:

School of Social Work

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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:

Dec 15, 2022

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Position Duration:

Expected to Continue Until Aug 31, 2024

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Location:

UT MAIN CAMPUS

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Job Details:

General Notes

This is a grant-funded position and reassignment will be based upon performance, progress toward research goals and continuation of funding.

Purpose

This is a grant-funded position to further research and development for health technology innovations focused in addiction and recovery services at the Addiction Research Institute (ARI) at The University of Texas at Austin. The – Principal Data Engineer (Data Intelligence Manager) will lead a team of researchers and work closely with faculty and software engineers to further the development and testing of a digital platform to improve real-time overdose data to inform community response efforts.

Responsibilities

• Manage and lead a team in research and development for grant-funded digital health products within the context of addiction, recovery, and overdose surveillance. Collaborate with an interdisciplinary team of technical and scientific experts, and collectively manage project progress.
• Work with and ingest large existing data sets and live data feeds, create aggregated database that can be used for predictive analytics and modeling. Participate in data collection exercises, data management, and analysis.
• Design and implement new features (e.g., advanced processing options, data visualization) for the digital platform.  Conduct user experience research and market validation of new features.
• Work with collaborating partners to improve interoperability of overdose and addiction-related data sources to be ingested into a robust opioid-specific data warehouse.
• Create and maintain supporting documentation for software and systems.  Provide guidance and assistance to junior employees.  Other duties as assigned.

Required Qualifications

Master’s degree in computer science, computer engineering, public health, psychology, or a related field. At least 3 years of applied research experience relevant to the purpose of the position. Expertise in developing various machine learning models including natural language processing, or ability to work with faculty experts in this space. Proven capacity for innovative, creative digital health product development. Must have a dynamic skill set. Willingness and ability to work with new technologies. Excellent organizational skills. Ability to plan and coordinate multiple tasks. Excellent time management skills. Excellent attention to detail. Effective problem solving skills and excellent judgment. Ability to work independently with sensitive and confidential information. Maintain professional demeanor. Work as a team member without daily supervision and effectively communicate with a diverse group of clients. Ability to work under deadlines and accept supervision. Regular and punctual attendance. Ability to work effectively within multiple disciplines, including data scientists, software developers, engineers, research faculty, and healthcare providers. Ability to implement the practical application of advanced data & analytics methodologies to health data related to substance use and overdose. Demonstrated team management and interpersonal communication skills. Values the contributions of others in a diverse work environment.

Relevant education and experience may be substituted as appropriate.

Preferred Qualifications

Doctoral Degree in computer science, computer engineering, public health, psychology, or a related field. More than 3 years of applied research experience relevant to the purpose of the position. Experience in the application of various advanced data & analytics and statistical methodologies to large healthcare data sets. Desire to research and develop products using new and innovative software technologies. Experience with algorithm development and software architecture. Prior work experience in professional or research-oriented software development.

Salary Range

$90,000 – $100,000 depending on qualifications

Working Conditions

• May work around standard office conditions.

• Repetitive use of a keyboard at a workstation

Work Shift

• M-F, Flexible between 8am-6pm

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.

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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.

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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.

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Background Checks:

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

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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.

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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.

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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.

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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:

• E-Verify Poster (English) [PDF]
• E-Verify Poster (Spanish) [PDF]
• Right To Work Poster (English) [PDF]
• Right To Work Poster (Spanish) [PDF]

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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.