Job Posting Title:
Data Engineer I----
Hiring Department:
Dell Medical School----
Position Open To:
All Applicants----
Weekly Scheduled Hours:
40----
FLSA Status:
Exempt----
Earliest Start Date:
Immediately----
Position Duration:
Expected to Continue----
Location:
AUSTIN, TX----
Job Details:
The Data Engineer is responsible for expanding and optimizing the healthcare system’s data and data pipeline architecture, as well as optimizing data flow and collection for cross-functional teams. This role designs, builds, and maintains scalable data infrastructure to support clinical, operational, and strategic decision-making. Reporting to the Director of Data Intelligence and Decision Science, the Data Engineer collaborates with data scientists, analysts, software engineers, and clinical informatics teams. This position ensures data quality, security, and accessibility by integrating data from different sources such as EHRs, medical devices, financial systems, and external partners. The Data Engineer is critical to enabling predictive analytics, population health management, and regulatory compliance.
Designs and Maintains Data Pipelines
Creates and maintains optimal data pipeline architecture for structured and unstructured healthcare data.
Assembles large, complex data sets that meet functional and non-functional business requirements.
Builds scalable ETL/ELT pipelines using SQL and AWS big data technologies.
Optimizes pipeline performance for latency, throughput, and fault tolerance.
Ensures pipelines comply with HIPAA and other regulatory standards.
Develops and Manages Data Infrastructure
Builds infrastructure for optimal extraction, transformation, and loading of data from diverse sources.
Creates and maintains data lakes, warehouses, and marts using platforms like Snowflake, Redshift, or BigQuery.
Configures cloud-based storage and compute environments (AWS, Azure, GCP).
Implements schema design, indexing, and partitioning strategies.
Ensures high availability and disaster recovery protocols.
Enables Analytics and Data Science
Creates data tools for analytics and data science teams to build and optimize data products.
Develops reusable components for reporting and dashboarding tools.
Builds data models and views for use by analysts and data scientists.
Enables self-service analytics through curated datasets.
Collaborates with stakeholders to define KPIs and metrics.
Improves Internal Processes and Scalability
Identifies, designs, and implements internal process improvements.
Automates manual processes and optimizes data delivery.
Re-designs infrastructure for greater scalability and performance.
Refactors legacy systems for maintainability.
Implements CI/CD pipelines for data workflows.
Collaborates Across Teams
Works with stakeholders including Executive, Product, Data, and Design teams to support data infrastructure needs.
Translates business requirements into technical specifications.
Provides mentorship to junior data engineers.
Communicates technical concepts to non-technical stakeholders.
Supports cross-functional initiatives and agile squads.
Ensures Data Governance and Security
Keeps data separate and secure, following all relevant data governance and security protocols.
Implements data validation, anomaly detection, and cleansing routines.
Collaborates with data governance teams to enforce policies.
Audits data for completeness, accuracy, and timeliness.
Supports data stewardship and master data management initiatives.
MARGINAL OR PERIODIC FUNCTIONS:
Conducts training sessions for analysts and clinical staff on data tools.
Participates in vendor evaluations and proof-of-concept projects.
Supports data integration for mergers, acquisitions, or new service lines.
Assists in disaster recovery drills and business continuity planning.
Contributes to grant proposals or research initiatives requiring data support.
Performs related duties as required.
Technical Learning
Quickly learns new technical skills and knowledge; is good at learning new industry, company, product, or technical knowledge.
Adopts new data tools and frameworks with minimal supervision.
Learns and applies healthcare-specific data standards (e.g., HL7, FHIR).
Keeps current with cloud platform updates and best practices.
Problem Solving
Uses rigorous logic and methods to solve difficult problems with effective solutions.
Diagnoses root causes of data pipeline failures.
Designs scalable solutions for complex data integration challenges.
Applies statistical methods to validate data quality.
Functional/Technical Skills
Possesses the functional and technical knowledge and skills to do the job at a high level of accomplishment.
Writes efficient SQL and Python code for data processing.
Configures cloud infrastructure for data workloads.
Implements secure and compliant data architectures.
Dealing with Ambiguity
Copes with change effectively; can shift gears comfortably; can decide and act without having the total picture.
Designs flexible data models for evolving clinical needs.
Navigates incomplete or inconsistent data sources.
Adapts to shifting priorities in fast-paced environments.
Collaborates
Works effectively with others to achieve shared goals; actively listens and communicates openly.
Partners with clinicians to understand data needs.
Participates in cross-functional agile teams.
Resolves conflicts between technical and business priorities.
Strategic Agility
Sees ahead clearly; can anticipate future consequences and trends accurately.
Designs data systems that scale with organizational growth.
Aligns data engineering efforts with enterprise analytics strategy.
Anticipates regulatory changes and prepares infrastructure accordingly.
Requires a Bachelor's Degree in Computer Science, Information Systems, Engineering, Statistics, or a related field with at least 2 year(s) of experience in data engineering, architecture, or ETL development.
Proficiency with big data tools (e.g., Hadoop, Spark, Kafka).
Experience with both SQL and NoSQL databases.
Skilled in data pipeline and workflow management tools.
Familiarity with AWS services, such as EC2, EMR, RDS, Redshift, Glue, DynamoDB.
Programming/scripting experience in Python, Java, C++, Scala, or similar.
Relevant education and experience may be substituted as appropriate.
Master's Degree in Data Engineering, Computer Science, or related field with at least 5 year(s) of experience in healthcare data engineering or analytics.
Advanced SQL skills and hands-on relational database work.
Expertise in building and optimizing big data pipelines using Python.
Experience managing data transformation, metadata, dependencies, and workload orchestration.
Understanding of message queuing, stream processing, and scalable data storage systems.
Strong project management skills.
LICENSES, REGISTRATIONS OR CERTIFICATIONS
None
AWS Certified Data Analytics
Certified Health Data Analyst (CHDA)
Project Management Professional (PMP)
$71,059.66 + depending on qualifications
Standard office equipment
Repetitive use of a keyboard
May be exposed to such occupational hazards as communicable diseases, blood borne pathogens, ionizing and non-ionizing radiation, hazardous medications and disoriented or combative patients, or others.
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.----
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.
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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. 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.
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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.
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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:
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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.