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Lead Data Engineer

Job in Austin, Travis County, Texas, 78716, USA
Listing for: University of Texas
Full Time position
Listed on 2026-02-07
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager
Job Description & How to Apply Below
* 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
* 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.
* 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, architectures, and standards are well-documented for reuse, governance, and knowledge continuity.
* Stay current with advancements in AI, data engineering, and Databricks ecosystem, evaluating new tools and frameworks for potential adoption.
* Pilot and promote innovative solutions such as AI-assisted data quality checks, data observability automation, and intelligent pipeline optimization.
* Perform other duties as assigned, contributing to the organization’s data-driven and AI-enabled transformation.
* 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 Git Hub 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.
* 8+ years of experience in Data Engineering or…
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