Lead Data Engineer

Job Posting Title: Lead Data Engineer ---- Hiring Department: Enterprise Technology - Data to Insights (D2I) ---- Position Open To: All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue Until Dec 19, 2026 ---- Location: Texas ---- Job Details: General Notes This is a fixed term position that is expected to continue for a 1-year limited term from start date with a possibility for extension. Flexible work arrangements are available for this position, including the ability to work 100% remotely. Remote work for individuals who reside outside Texas but within the United States and its territories will be considered and requires Central Office approval. This position provides life/work balance with typically a 40-hour work week and travel limited to training (e.g., conferences/courses). Enterprise Technology is dedicated to supporting the mission of the University of Texas at Austin of unlocking potential and preparing future leaders of the state. Your skills will make a difference. You’ll be working for a university that is internationally recognized for research and the work you do will make a difference in the lives of our students, faculty and staff. If you’re the type of person that wants to know your work has meaning and impact, you’ll like working for our campus. 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: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards   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. Purpose 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. Responsibilities Technical Leadership: Design, architect, and deliver production-grade, scalable data pipelines and AI-ready data platforms using Databricks, AWS cloud-native services and modern data engineering frameworks.  Lead end-to-end implementation of lakehouse data pipelines, ensuring performance, reliability, and cost efficiency.  Champion industry best practices for data engineering.  Conduct and participate in peer code reviews to maintain code quality and consistency across the team.  Proactively identify and resolve bottlenecks in data ingestion, transformation, and orchestration processes using Databricks Delta Live Tables, Spark optimization techniques, and workflow automation.  Implement systems for data quality, observability, governance, and compliance using tools such as Unity Catalog, Delta Lake, and data validation frameworks.  Lead technical knowledge-sharing sessions on topics such as AI/ML integration, data lakehouse architecture, and emerging data technologies.  Project Management: Define project milestones, timelines, and deliverables for data and AI initiatives, ensuring timely and high-quality outcomes.  Collaborate with both internal and external stakeholders such as data architects, system architects, business users, Agile team members, and other D2I internal groups.  Manage project priorities, sprint planning, and team workloads while balancing innovation with delivery.  Communicate risks, dependencies, and resource constraints effectively, and develop mitigation plans for on-time project delivery.  Team Management and Leadership: Supervise and mentor a team of Data Engineers (2–5 individuals) working on cloud, Databricks, and AI pipeline initiatives.  Foster a culture of continuous learning, experimentation, and technical excellence, encouraging engineers to explore AI and automation use cases.  Participate in recruiting, onboarding, and developing data engineering talent with strong Databricks and AI skillsets.  Conduct performance reviews, set development goals, and create individualized growth plans for team members.  Encourage collaboration across Data, AI/ML, Analytics, and Infrastructure teams to drive cross-functional success.  Communication: Provide regular updates on project progress, technical challenges, and project milestones to both technical and business stakeholders.  Translate complex technical concepts related to Databricks, AI, and data architecture into clear narratives for non-technical audiences.  Foster a transparent communication culture and provide actionable feedback to promote a growth mindset.  Ensure all data engineering processes, architect