Job Details

Lead Data Engineer

The Lead 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 lead senior data engineers and data engineers to create complex data pipelines within 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 within the team and outside partners.

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

The University of Texas at Austin and Enterprise Technology provide an outstanding benefits package to our staff. Those benefits include:

• 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

Must be authorized to work in the United States on a full-time basis for any employer without sponsorship.

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

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or equivalent professional experience.
• 5+ years of experience designing, implementing, and optimizing complex, production-grade data pipelines or enterprise-scale data platforms.
• 5 years of experience in cloud-based data engineering using Databricks and Amazon Web Services (AWS) (e.g., Glue, S3, Lambda, Redshift).
• 3+ years of experience managing or leading teams of data and/or software engineers, including mentorship, performance management, and project delivery.
• Expertise in Python, PySpark, and SQL, with strong understanding of data modeling, stored procedures, and scalable data transformations.
• Proven experience architecting and implementing ETL/ELT solutions across relational, non-relational, and lakehouse environments (e.g., Delta Lake, Parquet, or Iceberg).
• Experience designing and managing CI/CD pipelines and infrastructure as code (IaC) using tools such as Databricks Repos, CDK, Terraform, or GitHub Actions.
• Demonstrated knowledge of test-driven development (TDD) and data quality frameworks, ensuring reliability and reproducibility across data workflows.
• Deep understanding of data governance, security, and compliance standards in cloud environments.
• Excellent analytical, problem-solving, and debugging skills across distributed data systems.
• Proven ability to communicate complex technical concepts clearly to both technical and non-technical audiences.
• Experience supervising, mentoring, and guiding junior team members on technical and professional development.

Equivalent combination of relevant education and experience may be substituted as appropriate.

Preferred Qualifications

• 8+ years of experience in Data Engineering or related fields, including 5+ years of hands-on experience building and optimizing data pipelines on Databricks or similar large-scale data platforms.
• Proven experience implementing lakehouse architectures leveraging Databricks Delta Lake, Delta Live Tables, and Unity Catalog for governance and scalability.
• Experience designing AI-ready data platforms and integrating machine learning pipelines using tools such as MLflow or model registry frameworks.
• 3+ years of experience managing or leading cross-functional technical teams, fostering collaboration between Data Engineering, Analytics, and AI/ML teams.
• 5+ years of experience with Agile software development methodologies and project tracking systems such as JIRA.
• Expertise in distributed data processing and streaming frameworks, such as Apache Spark, Kafka, Flink, or Airflow, for orchestration and automation.
• Strong familiarity with data observability, cost optimization, and performance tuning in Databricks and cloud-native architecture.
• Professional certifications such as Databricks Certified Data Engineer Professional or AWS Solutions Architect or AWS Data Analytics Specialty are highly desirable.
• Demonstrated ability to introduce new technologies and best practices to modernize existing data environments and promote AI/analytics maturity across the organization.
• Passion for continuous learning and staying current with emerging technologies in data engineering, AI integration, and Databricks ecosystem advancements.

Salary Range

$125,000 - $143,712

Working Conditions

• May work around standard office conditions
• Repetitive use of a keyboard at a workstation
• Use of manual dexterity (ex: using a mouse)

Work Shift

• Monday Friday 8am-5pm; Occasional nights or weekends may be required

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.