Senior Data Engineer
The University of Texas at Austin6 days ago
Base Salary
$138k - $138k/yr
Responsibilities
- Design, build, maintain, and optimize complex ETL/ELT pipelines for structured and unstructured data.
- Integrate data from EHRs, financial systems, registries, and external sources using batch and near-real-time processing patterns.
- Own and evolve data lake, warehouse, data mart, data modeling, schema, and partitioning architectures.
- Ensure data pipelines and platforms meet performance, reliability, fault-tolerance, cost-efficiency, regulatory, privacy, security, availability, scalability, and disaster recovery requirements.
- Build curated analytics-ready datasets and reusable data assets for analysts and data scientists.
- Support feature engineering, model training, deployment workflows, predictive analytics, and AI/ML proof-of-concept initiatives.
- Improve data engineering workflows through automation, monitoring, CI/CD, legacy refactoring, testing, documentation, and version control.
- Establish engineering standards and evaluate new data tools and technologies.
- Mentor Data Engineers, review code and architecture, provide technical guidance, and support onboarding and knowledge sharing.
- Lead data engineering workstreams and medium-to-large initiatives while translating stakeholder requirements into technical solutions.
- Support data integrations for new service lines, acquisitions, migrations, vendor evaluations, disaster recovery testing, business continuity planning, grants, and research initiatives.
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or a related field.
- At least 6 years of experience in data engineering, analytics engineering, or data platform development.
- Demonstrated experience designing and leading complex data pipelines and data platforms.
- Advanced proficiency in SQL and Python and related data engineering languages.
- Strong experience with distributed data processing frameworks such as Spark and workflow orchestration tools such as Airflow.
- Deep familiarity with cloud-based data platforms and services including AWS, GCP, or Azure/Fabric.
- Experience designing and optimizing data models for analytics and reporting.
- Strong understanding of data governance, data quality, security best practices, and regulated data environments.
- Preferred experience with healthcare or clinical data and healthcare standards such as HL7 and FHIR.
- Preferred exposure to AI/ML infrastructure, feature stores, or model operationalization.
- Preferred experience leading technical initiatives or acting as a team lead.
- Relevant education and experience may be substituted as appropriate.
- Preferred master's degree in Data Science, Data Engineering, Computer Science, Informatics, or a related field.
- Preferred cloud certifications including Microsoft Certified: Azure Data Engineer Associate, Google Cloud Professional Data Engineer, or AWS Certified Data Analytics – Specialty.
Benefits
- Regular staff position expected to continue, with an immediate start date and 40 scheduled hours per week.
- Located in Austin, Texas; standard office equipment and repetitive keyboard use are required, with possible healthcare-related occupational hazards depending on assignment.
- Eligible positions participate in the Teacher Retirement System of Texas subject to the stated hours and duration requirements.
- A criminal history background check is required for finalists.
- Employment requires completion of the federal I-9 process and verification of authorization to work in the United States.
Tech Stack
Categories
Data Engineering
About The University of Texas at Austin
UT Health Austin is the clinical practice of Dell Medical School at The University of Texas at Austin, providing primary and specialty care to patients in Central Texas. It operates multidisciplinary clinics across areas such as orthopedics, women’s health, pediatrics, oncology, gastroenterology, endocrinology, infectious disease, and ophthalmology, and bills through insurance and self-pay. Established in 2017 and based in Austin, it integrates care with UT Austin research and training programs.