Data Scientist jobs at Univ. Of Texas Cancer Ctr.

Job Posting Title: Principal Data Engineer * --- Hiring Department: Enterprise Technology - Data to Insights (D2I) * --- All Applicants * --- Weekly Scheduled Hours: 40 * --- FLSA Status: Exempt * --- * --- 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: ****************************************** 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. Purpose The Principal 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 be responsible for leading the data engineering team to innovate and implement the newest data engineering trends and best practices to create complex data pipelines withing 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 particular position has a heavy emphasis on Databricks and AI Readiness. Responsibilities Technical Leadership: * Architect, design, and lead the development of enterprise-scale, production-grade data platforms and pipelines using Databricks and cloud-native technologies (AWS, Azure, or GCP). * Champion the adoption of the Databricks Lakehouse architecture to unify data warehousing, data science, and machine learning workloads across the organization. * Guide the design and deployment of AI-ready data pipelines to support predictive analytics, generative AI, and advanced decision intelligence use cases. * Define and enforce data engineering standards, including performance optimization, scalability, data observability, and cost efficiency. * Oversee code reviews, architecture reviews, and system design discussions to ensure technical excellence and maintainability across the engineering team. * Lead the implementation of robust data quality, governance, and compliance frameworks, leveraging Databricks Unity Catalog and modern metadata management tools. * Solve complex data architecture and integration challenges using advanced technologies such as Spark, Delta Live Tables, Airflow, and MLflow. * Drive the development of automated, CI/CD-enabled data workflows and promote best practices in data infrastructure as code (IaC) and DevOps for data. Project Management & Collaboration: * Provide strategic technical leadership and mentorship to data engineering teams, fostering a collaborative environment that promotes innovation, accountability, and growth. * Collaborate closely with data architects, AI/ML engineers, and analytics teams to align data solutions with organizational goals and research initiatives. * Engage with cross-campus and cross-departmental technical groups to evangelize modern data practices and accelerate AI transformation initiatives. * Lead knowledge-sharing sessions and architecture reviews on emerging data engineering trends, Databricks advancements, and AI integration techniques. Communication: * Effectively communicate technical strategies, project status, risks, and architecture decisions to both technical and non-technical stakeholders. * Translate complex data engineering concepts into clear business impacts, helping decision-makers understand opportunities and trade-offs. * Produce clear and detailed technical documentation, design specifications, and operational playbooks to support long-term scalability and training. * Advocate for data engineering as a foundational enabler of AI, analytics, and digital transformation initiatives across the institution. Innovation: * Lead research and development efforts to evaluate and implement cutting-edge technologies within the Databricks ecosystem and broader AI/data landscape. * Conduct feasibility studies and proofs of concept (POCs) for next-generation architectures involving AI model integration, real-time streaming, and intelligent automation. * Partner with academic, administrative, and campus stakeholders to pilot AI-enabled data systems, such as model-assisted data validation and automated feature generation. * Stay ahead of emerging trends in data engineering, AI readiness, and cloud infrastructure, continuously recommending and implementing innovative solutions. Other: * Contribute to recruitment, hiring, and onboarding of new data engineering team members. * Represent the data engineering function in strategic planning discussions and cross-organizational technology initiatives. * Perform other duties as assigned, aligned with the mission to build a secure, scalable, and AI-enabled data ecosystem. 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 maintaining complex, production-grade data pipelines and enterprise data platforms. * 5+ years of hands-on experience with cloud-based data engineering, preferably in Amazon Web Services (AWS), with strong command of services such as Glue, S3, Lambda, Redshift, and EMR. * 3+ years of experience defining cloud data architecture and data strategy in large, distributed enterprise environments. * Deep expertise with Databricks Lakehouse Platform, including Delta Lake, Delta Live Tables, and Unity Catalog, for scalable data ingestion, transformation, and governance. * Proficiency in Python, PySpark, and SQL, with demonstrated experience in building ETL/ELT workflows across structured and unstructured data sources. * Proven ability to design and implement high-performance, AI-ready data architectures supporting analytics, machine learning, and real-time data processing. * Experience developing and deploying Continuous Integration / Continuous Delivery (CI/CD) pipelines for data engineering using tools such as Databricks Repos, GitHub Actions, or Terraform. * Strong foundation in test-driven data engineering, including automated data quality, validation, and observability frameworks. * Advanced knowledge of data governance, metadata management, and security compliance in cloud and Databricks environments. * Excellent systems analysis, design, and troubleshooting skills with the ability to address performance bottlenecks in distributed data systems. * Exceptional communication skills, with the ability to convey complex technical concepts clearly to both technical and non-technical stakeholders. * Proven experience leading and mentoring teams, fostering technical excellence and innovation. * Self-motivated and capable of working independently in a dynamic, evolving technology landscape. Equivalent combination of relevant education and experience may be substituted as appropriate. Preferred Qualifications * 10+ years of experience in Data Engineering, Data Architecture, or related fields, including 5+ years of hands-on work with Databricks or equivalent large-scale data platforms. * Demonstrated experience architecting and optimizing Lakehouse environments that integrate data science, analytics, and AI workloads. * Proven success in implementing AI/ML-ready data pipelines and collaborating with Data Scientists and MLOps teams using tools like MLflow, Feature Store, or model registries. * 5+ years of experience applying Agile software development methodologies and using tools such as JIRA, Confluence, or Azure DevOps for project tracking and delivery. * Expertise in distributed data processing and streaming technologies such as Apache Spark, Kafka, Flink, or Airflow for orchestration and automation. * Experience designing and operationalizing data observability and cost optimization strategies within Databricks and cloud environments. * Strong understanding of data mesh, data fabric, and modern metadata management principles for large-scale organizations. * Professional certifications such as Databricks Certified Data Engineer Professional, AWS Solutions Architect, or AWS Data Analytics Specialty are highly desirable. * Demonstrated ability to drive innovation, introduce emerging technologies, and lead proofs of concept (POCs) for AI integration, automation, or advanced analytics. * Commitment to continuous learning and technology leadership, staying current with advancements in Databricks, AI engineering, and modern cloud data ecosystems. 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. * --- 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. * --- 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. * --- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. * --- 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. * --- 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. * --- 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. * --- 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 and Spanish) [PDF] * Right to Work Poster (English) [PDF] * Right to Work Poster (Spanish) [PDF] * --- 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.

Job Posting Title: Lead Data Engineer * --- Hiring Department: Enterprise Technology - Data to Insights (D2I) * --- All Applicants * --- Weekly Scheduled Hours: 40 * --- FLSA Status: Exempt * --- * --- 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: ****************************************** 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. 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, architectures, and standards are well-documented for reuse, governance, and knowledge continuity. Innovation and Other Duties: * 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. 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. * --- 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. * --- 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. * --- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. * --- 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. * --- 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. * --- 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. * --- 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 and Spanish) [PDF] * Right to Work Poster (English) [PDF] * Right to Work Poster (Spanish) [PDF] * --- 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.

Job Posting Title: Senior Data Engineer * --- Hiring Department: Enterprise Technology - Data to Insights (D2I) * --- All Applicants * --- Weekly Scheduled Hours: 40 * --- FLSA Status: Exempt * --- * --- 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: ****************************************** 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. Purpose The Senior 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 create complex data pipelines into 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. Responsibilities Data Engineering: * Lead the design, development, and automation of scalable, high-performance data pipelines across institutional systems, AWS, Databricks, and external vendor APIs. * Implement Databricks Lakehouse architectures to unify structured and unstructured data, enabling AI-ready data platforms that support advanced analytics and machine learning use cases. * Build robust and reusable ETL/ELT workflows using Databricks, Spark, Delta Lake, and Python to support batch and streaming integrations. * Ensure performance, reliability, and data quality of data pipelines through proactive monitoring, optimization, and automated alerting. * Partner with business and technical stakeholders to define and manage data pipeline parameters-including load frequency, transformation logic, and delivery mechanisms-ensuring alignment with analytical and AI goals. * Ensure all data engineering solutions adhere to university security, compliance, and governance guidelines, while leveraging best practices in cloud-native data development. * Develop and maintain comprehensive technical documentation of data pipeline designs, data flows, and operational procedures. * Collaborate with enterprise data architects, data modelers, data stewards, and subject matter experts to ensure data consistency, lineage, and semantic alignment across the ecosystem. * Continuously evaluate and introduce emerging technologies-such as Databricks Unity Catalog, MLflow, Delta Live Tables, and AI-driven data observability tools-to enhance the data engineering landscape. * Drive innovation by modernizing existing pipelines toward AI-readiness, enabling future integration with predictive analytics and machine learning models. * Stay current with advances in Databricks, AI-driven data engineering, and cloud technologies, and advocate for their responsible adoption. * Contribute to the vision of building a modern, AI-ready data ecosystem that powers advanced analytics, automation, and decision intelligence across the University. Collaboration, Support, & Communication: * Work both independently and collaboratively within cross-functional teams to deliver data products and pipelines that meet the University's evolving data and analytics needs. * Communicate clearly and effectively with technical and non-technical stakeholders regarding project progress, risks, dependencies, and technical challenges. * Promote collaboration and knowledge sharing within the Data Engineering team through brainstorming sessions, design reviews, and Databricks best-practice discussions. * Foster a culture of learning and innovation, supporting team morale and professional growth. * Provide mentorship and peer guidance to junior data engineers on data pipeline design, Databricks workflows, and coding best practices. * Participate in change management processes to ensure transparency and coordination across teams during system enhancements or platform migrations. Perform other related functions as assigned. Required Qualifications * Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent professional experience. * At least two years of hands-on experience in Data Engineering using cloud-based platforms (AWS, Azure, or GCP) with emphasis on Databricks or Spark-based pipelines. * Proven experience in designing, building, and automating scalable, production-grade data pipelines and integrations across multiple systems and APIs. * Proficiency in Python and SQL, with demonstrated ability to write efficient, reusable, and maintainable code for data transformations and automation. * Strong knowledge of ETL/ELT principles, data lakehouse architectures, and data quality monitoring. * Experience implementing and maintaining CI/CD pipelines for data workflows using modern DevOps tools (e.g., GitHub Actions, Azure DevOps, Jenkins). * Familiarity with data governance, security, and compliance practices within cloud environments. * Strong analytical, troubleshooting, and performance optimization skills for large-scale distributed data systems. * Excellent communication and collaboration skills to work effectively with technical and non-technical stakeholders. * Demonstrated experience mentoring and guiding junior engineers or peers on technical projects. Equivalent combination of relevant education and experience may be substituted as appropriate. Preferred Qualifications * Five or more years of experience in Data Engineering or related fields with increasing technical leadership responsibilities. * Three or more years of experience developing and optimizing data pipelines on Databricks, including Delta Lake, Delta Live Tables, and Databricks Workflows. * Experience designing AI-ready data architectures and integrating data workflows with machine learning and analytics environments. * Experience with distributed data processing frameworks such as Spark, Kafka, or Flink. * Databricks or AWS certifications (e.g., Databricks Certified Data Engineer Professional, AWS Solutions Architect, or AWS Data Analytics Specialty). * Two or more years of experience in Agile software development environments, including use of tools such as JIRA, Confluence, or similar for issue tracking and project management. * Hands-on experience with data orchestration tools (e.g., Airflow, Databricks Workflows, or AWS Step Functions). * Exposure to data governance frameworks and AI/ML operations (MLOps) concepts such as MLflow or model monitoring. * Demonstrated ability to lead or supervise small teams or project-based technical efforts. * Passion for continuous learning and staying current with advancements in Databricks, cloud-based data engineering, and AI enablement. Salary Range $115,000 - $124,968 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. * --- 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. * --- 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. * --- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. * --- 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. * --- 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. * --- 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. * --- 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 and Spanish) [PDF] * Right to Work Poster (English) [PDF] * Right to Work Poster (Spanish) [PDF] * --- 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.

Job Posting Title: Data Engineer Manager ---- Hiring Department: Dell Medical School ---- All Applicants ---- Weekly Scheduled Hours: 40 ---- FLSA Status: Exempt ---- Earliest Start Date: Immediately ---- Position Duration: Expected to Continue ---- Location: AUSTIN, TX ---- Job Details: Purpose The Data Engineer Manager leads a team of data engineers responsible for designing, building, and maintaining scalable data infrastructure and pipelines that support clinical, operational, and financial analytics across the healthcare system. This role collaborates closely with data scientists, software engineers, business intelligence analysts, and clinical informatics teams to ensure data is accessible, accurate, and secure. Reporting to the Director of Data Systems and Analytics, the position plays a critical role in enabling data-driven decision-making and innovation in a complex healthcare environment. Responsibilities Data Architecture & Pipeline Management Designs and oversees scalable data pipelines for structured and unstructured data across clinical, operational, and financial systems. Manages ETL/ELT processes using tools such as Apache Spark, Kafka, Airflow, and other modern orchestration platforms. Ensures data integrity, availability, and performance across cloud and on-premise platforms. Implements and maintains data lake and warehouse solutions (e.g., Snowflake, BigQuery, Redshift). Collaborates with infrastructure and application teams to optimize data flow and storage. Team Leadership & Development Recruits, mentors, and manages a team of data engineers, fostering a high-performance and inclusive team culture. Conducts performance evaluations, sets development goals, and supports career progression. Promotes collaboration, innovation, and continuous learning through team meetings, code reviews, and knowledge-sharing sessions. Aligns team goals with organizational priorities and strategic initiatives. Ensures adherence to engineering best practices and coding standards. Stakeholder Collaboration & Requirements Gathering Works closely with clinical, operational, and financial stakeholders to define data needs and translate business requirements into technical specifications. Facilitates cross-functional communication between IT, analytics, clinical informatics, and business intelligence teams. Leads discovery sessions and data mapping exercises to ensure alignment between data engineering deliverables and business objectives. Supports the development of dashboards, reports, and predictive models by enabling access to clean, well-structured data. Data Governance & Compliance Ensures adherence to HIPAA, HITECH, and internal data governance policies, including data privacy and security protocols. Implements data security measures, access controls, and encryption standards across all data platforms. Supports audit readiness and regulatory reporting by maintaining accurate metadata and lineage documentation. Collaborates with data governance and compliance teams to establish and enforce data quality standards. Strategic Planning & Innovation Contributes to the development and execution of the enterprise data strategy and roadmap. Evaluates emerging technologies and recommends adoption to improve scalability, performance, and cost-efficiency. Aligns data engineering initiatives with strategic goals of the healthcare system, including population health, value-based care, and operational excellence. Participates in long-term planning for data infrastructure modernization and cloud migration. Budget & Resource Management Manages the data engineering team's operational budget, including software licenses, cloud services, training, and professional development. Tracks resource utilization and optimizes operational efficiency through capacity planning and workload balancing. Supports vendor selection, contract negotiations, and license renewals for data platforms and tools. Provides input into capital planning and technology investment decisions. Marginal or Periodic Functions: Participates in enterprise-wide data governance committees. Presents at internal and external conferences or forums. Assists in grant writing or research data infrastructure proposals. Conducts periodic system performance audits. Adheres to internal controls and reporting structure. Performs related duties as required. Knowledge/Skills/Abilities Manages Complexity Breaks down ambiguous problems into manageable components. Uses multiple data sources to inform decisions. Designs scalable solutions for evolving data needs. Tech Savvy Evaluates and integrates new tools (e.g., cloud platforms). Encourages experimentation and innovation. Maintains fluency in modern data engineering stacks. Collaborates Facilitates cross-functional meetings. Resolves conflicts constructively. Shares credit and fosters team cohesion. Plans and Aligns Develops clear project plans and milestones. Communicates expectations effectively. Adjusts plans based on feedback and performance. Ensures Accountability Tracks progress and outcomes. Provides timely feedback. Establishes clear roles and responsibilities. Strategic Mindset Anticipates future data needs. Aligns technical decisions with business strategy. Identifies long-term opportunities for data innovation. Required Qualifications Bachelor's degree in Computer Science, Information Systems, or related field. 10 years of experience in data engineering or data architecture including designing data architectures, developing data pipelines, implementing data quality, and performance monitoring. 2 years of experience in a technical leadership or team lead role with a track record of delivering complex data projects and mentoring junior engineers in a fast-paced department. Experience in healthcare data systems (e.g., EHR, claims, HL7, FHIR). Relevant education and experience may be substituted as appropriate. Preferred Qualifications Master's degree in Data Science, Engineering, or Healthcare Informatics. 7+ years of progressive experience in data engineering. Experience with cloud platforms (e.g., GCP, AWS, Azure). Salary Range $135,000+ depending on qualifications Working Conditions Standard office conditions. 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. ---- 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. ---- 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. ---- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. ---- 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. ---- 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. ---- 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. ---- 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 and Spanish) [PDF] Right to Work Poster (English) [PDF] Right to Work Poster (Spanish) [PDF] ---- 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.

Job Posting Title: RESA III - Geoscience Data and Collections Engineer/Geoscientist * --- Hiring Department: Bureau of Economic Geology * --- All Applicants * --- Weekly Scheduled Hours: 40 * --- FLSA Status: Exempt * --- * --- Position Duration: Expected to Continue * --- Location: PICKLE RESEARCH CAMPUS * --- Job Details: General Notes The Resource Center at the Bureau of Economic Geology (Bureau) houses an extensive archive of geologic information dating back to the 1870s. This collection includes print and digital records of geological and geophysical data such as maps, well logs, engineering and geologic reports, photographs, field notes, and samples. Many of these materials are original works by Bureau researchers and other geoscientists who have contributed their collections over the years. In addition, the Bureau houses an extensive core collection comprising more than 2 million boxes of core and other sample materials from various geographic locations across the United States, as well as a few international locations. The collection is maintained at two core facilities located in Austin and Houston. This position is in-person at the J.J. Pickle Research Campus in North Austin. Purpose The Bureau of Economic Geology is seeking a highly motivated and technically skilled Geoscience Data and Collections Engineer/Geoscientist to lead the design, implementation, and maintenance of systems for cataloging and managing the Bureau's archive collections and physical rock materials (core, cuttings, thin sections and rock samples) and associated well and subsurface data, including paper logs, reports, etc. This role requires a unique combination of geoscience knowledge and data science expertise to support the long-term preservation, accessibility, and usability of one of the largest geologic collections in the world. Responsibilities * Process, organize, and describe physical and digital archival collections, including maps, field notes, photographs, unpublished reports, and a wide range of geological and geophysical data types. * Design and maintain robust digital systems for cataloging and managing geological archive records, samples and associated metadata. * Collaborate with geoscientists, IT staff, and collection managers to ensure data integrity, accessibility, and scalability. * Develop and implement workflows for digitizing, tagging, and integrating archive records, paper logs and other analog records. * Lead efforts to modernize legacy data systems and migrate data to new platforms as needed. * Ensure compliance with data standards and best practices in geoscience informatics. * Provide technical support and training to staff and researchers using the collections database. * Contribute to strategic planning for long-term data stewardship and digital infrastructure. * Provides research support by facilitating access to archival records for scholars, scientists, and the public, supporting research initiatives, and public engagement with institutional resources. * Supports Bureau researchers and donors in the submission and integration of new archival records, ensuring accurate documentation and incorporation into the existing archive. * Collaborates with the Resource Center Manager, Resource Center System Specialist, and researchers to enhance the Bureau's archival database. Required Qualifications * Bachelor's degree in Geoscience, Earth Sciences or equivalent with four years of experience and a Master's degree in Geosciences, Geoinformatics, or Data Science with two years of experience * Strong understanding of geological sample types and well data (e.g., cores, cuttings, thin sections, and well-logs). * Experience with database design, data modeling, and data management systems. * Proficiency in programming or scripting languages (e.g., Python, SQL) for data handling and automation. * Familiarity with GIS, metadata standards, and digital archiving best practices. * Excellent problem-solving skills and ability to work independently and collaboratively. * Ability to interact with others in a respectful, patient, and friendly manner when working with staff and visitors. * Occasional travel for work * The applicant for the job should have a valid Texas driver's license and a good driving record and should take the UT-mandated online driver training modules to remain authorized to drive Bureau vehicles. Preferred Qualifications * Library science training and/or archive experience * Experience working with geological collections or in a research repository environment. * Knowledge of cloud-based data storage and management solutions. * Experience with data visualization tools and dashboards. * Familiarity with academic or government research environments Salary Range $60,000+ depending on qualifications Working Conditions * May work around standard office conditions * Repetitive use of a keyboard at a workstation * Use of manual dexterity * Climbing of stairs * Climbing of ladders * Lifting and moving * Occasional weekend, overtime, and evening work to meet deadline Required Materials * Resume/CV * 3 work references with their contact information * Letter of interest * --- 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. * --- 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. * --- Background Checks: A criminal history background check will be required for finalist(s) under consideration for this position. * --- 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. * --- 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. * --- 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. * --- 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 and Spanish) [PDF] * Right to Work Poster (English) [PDF] * Right to Work Poster (Spanish) [PDF] * --- 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.